I have some RGB(image) data which is 12 bit. Each R,G,B has 12 bits, total 36 bits.
Now I need to club this 12 bit RGB data into a packed data format. I have tried to mention the packing as below:-
At present I have input data as -
B0 - 12 bits G0 - 12 bits R0 - 12 bits B1 - 12 bits G1 - 12 bits R1 - 12 bits .. so on.
I need to convert it to packed format as:-
Byte1 - B8 (8 bits of B0 data)
Byte2 - G4B4 (remaining 4 bits of B0 data+ first 4 bits of G0)
Byte3 - G8 (remaining 8 bits of G0)
Byte4 - R8 (first 8 bits of R0)
Byte5 - B4R4 (first 4 bits of B1 + last 4 bits of R0)
I have to write these individual bytes to a file in text format. one byte below another.
Similar thing i have to do for a 10 bit RGB input data.
Is there any tool/software to get the conversion of data i am looking to get done.
I am trying to do it in a C program - I am forming a 64 bit from the individual 12 bits of R,G,B (total 36 bits). But after that I am not able to come up with a logic to pick
the necessary bits from a R,G,B data to form a byte stream, and to dump them to a text file.
Any pointers will be helpful.
This is pretty much untested, super messy code I whipped together to give you a start. It's probably not packing the bytes exactly as you want, but you should get the general idea.
Apologies for the quick and nasty code, only had a couple of minutes, hope it's of some help anyway.
#include <stdio.h>
typedef struct
{
unsigned short B;
unsigned short G;
unsigned short R;
} UnpackedRGB;
UnpackedRGB test[] =
{
{0x0FFF, 0x000, 0x0EEE},
{0x000, 0x0FEF, 0xDEF},
{0xFED, 0xDED, 0xFED},
{0x111, 0x222, 0x333},
{0xA10, 0xB10, 0xC10}
};
UnpackedRGB buffer = {0, 0, 0};
int main(int argc, char** argv)
{
int numSourcePixels = sizeof(test)/sizeof(UnpackedRGB);
/* round up to the last byte */
int destbytes = ((numSourcePixels * 45)+5)/10;
unsigned char* dest = (unsigned char*)malloc(destbytes);
unsigned char* currentDestByte = dest;
UnpackedRGB *pixel1;
UnpackedRGB *pixel2;
int ixSource;
for (ixSource = 0; ixSource < numSourcePixels; ixSource += 2)
{
pixel1 = &test[ixSource];
pixel2 = ((ixSource + 1) < numSourcePixels ? &test[ixSource] : &buffer);
*currentDestByte++ = (0x0FF) & pixel1->B;
*currentDestByte++ = ((0xF00 & pixel1->B) >> 8) | (0x0F & pixel1->G);
*currentDestByte++ = ((0xFF0 & pixel1->G) >> 4);
*currentDestByte++ = (0x0FF & pixel1->R);
*currentDestByte++ = ((0xF00 & pixel1->R) >> 8) | (0x0F & pixel2->B);
if ((ixSource + 1) >= numSourcePixels)
{
break;
}
*currentDestByte++ = ((0xFF0 & pixel2->B) >> 4);
*currentDestByte++ = (0x0FF & pixel2->G);
*currentDestByte++ = ((0xF00 & pixel2->G) >> 8) | (0x0F & pixel2->R);
*currentDestByte++ = (0xFF0 & pixel2->R);
}
FILE* outfile = fopen("output.bin", "w");
fwrite(dest, 1, destbytes,outfile);
fclose(outfile);
}
Use bitwise & (and), | (or), and shift <<, >> operators.
Related
I got a 16 bpp bitmap that I converted to 32 bpp via code below:
void Rgb555ToRgb8(const UChar* bitmapData, UInt32 width, UInt32 height, UChar* buf)
{
UInt32 dst_bytes_per_row = width * 4;
UInt32 src_bytes_per_row = ((width * 16 + 31) / 32) * 4;
UInt16 red_mask = 0x7C00;
UInt16 green_mask = 0x3E0;
UInt16 blue_mask = 0x1F;
for (UInt32 row = 0; row < height; ++row)
{
UInt32 dstCol = 0, srcCol = 0;
do
{
UInt16 rgb = *(UInt16*)(bitmapData + row * src_bytes_per_row + srcCol);
UChar red_value = (rgb & red_mask) >> 10;
UChar green_value = (rgb & green_mask) >> 5;
UChar blue_value = (rgb & blue_mask);
buf[row*dst_bytes_per_row + dstCol] = blue_value << 3;
buf[row*dst_bytes_per_row + dstCol + 1] = green_value << 3;
buf[row*dst_bytes_per_row + dstCol + 2] = red_value << 3;
buf[row*dst_bytes_per_row + dstCol + 3] = rgb >> 15;
srcCol += 2;
dstCol += 4;
} while (srcCol < src_bytes_per_row);
}
}
Here is conversion result: [2]: https://i.stack.imgur.com/1ajO7.png
I also tried to convert this image via GdiPlus:
Gdiplus::Bitmap* bmp = new Gdiplus::Bitmap(w,h,PixelFormat32bppRGB);
Resultant image is .
Notice that the 2 results don't look exactly the same (e.g., the background in GdiPlus result is white). How can I modify my code to match GdiPlus result?
There are two issues that need to be addressed:
Unused bits
When moving from 5 bits of information to 8 bits of information you gain an additional 3 bits. As implemented, the code doesn't make use of that additional range, and is biased towards darker color components. This is an illustration of what blue_value << 3 actually does:
5 bits per channel 8 bits per channel
bbbbb -> bbbbb000
To address this, the least significant 3 bits need to grow as the channel value gets higher. A simple (yet somewhat inaccurate) would be to just copy the most significant 3 bits down to the least significant 3 bits, i.e.
buf[row*dst_bytes_per_row + dstCol] = (blue_value << 3) | (blue_value >> 2);
buf[row*dst_bytes_per_row + dstCol + 1] = (green_value << 3) | (green_value >> 2);
buf[row*dst_bytes_per_row + dstCol + 2] = (red_value << 3) | (red_value >> 2);
The exact mapping would be a bit more involved, something like
blue_value = static_cast<UChar>((blue_value * 255.0) / 31.0 + 0.5);
That converts from 5 bits to the respective 8 bit value that's nearest to the ideal value, including the 4 values that were 1/255th off in the bit-shifting solution above.
If you opt for the latter, you can build a lookup table that stores the mapped values. This table is only 32 entries of one byte each, so it fits into a single cache-line.
Alpha channel
Assuming that the MSB of your source image is indeed interpreted as an alpha value, you're going to have move that into the destination as well. Since the source is only 1 bit of information, the raw transformation is trivial:
buf[row*dst_bytes_per_row + dstCol + 3] = rgb & (1 << 15) ? 255 : 0;
That may or may not be all that's needed. Windows assumes premultiplied alpha, i.e. the stored values of the color channels must be premultiplied by the alpha value (see BLENDFUNCTION for reference).
If the alpha value is 255, the color channel values are already correct. If the alpha value is 0, all color channels need to be multiplied by zero (or simply set to 0). The translation doesn't produce any other alpha values.
I am using the following function to extract n bits from a number. I got this function from here. For convenience I am posting it here. I would like to obtain bits from 0 to 9 and then in another statement bits 10 to 15. I am passing in 1033. I get the correct value of bits 0 to 9 but incorrect value for 10 to 15. I should get a 1 instead i am getting 1024 any suggestions ?
unsigned createMask(unsigned a, unsigned b)
{
unsigned r = 0;
for (unsigned i = a; i <= b; i++)
r |= 1 << i;
return r;
}
Now i have this
unsigned short langId = 1033 ;// 10000001001
unsigned primary = createMask(0,9) & langId; //gives 9 correct
unsigned sec = createMask(10,15) & langId; //gives 1024 incorrect should be 1
The bits of sec that you've set are still in the 10-15 bit positions. You need to shift them back towards the start. Otherwise you have a single 1 set at position 10 and 210 is giving your answer of 1024
sec >> 10
Demo
I am solving this problem:
The count of ones in binary representation of integer number is called the weight of that number. The following algorithm finds the closest integer with the same weight. For example, for 123 (0111 1011)₂, the closest integer number is 125 (0111 1101)₂.
The solution for O(n)
where n is the width of the input number is by swapping the positions of the first pair of consecutive bits that differ.
Could someone give me some hints for solving in it in O(1) runtime and space ?
Thanks
As already commented by ajayv this cannot really be done in O(1) as the answer always depends on the number of bits the input has. However, if we interpret the O(1) to mean that we have as an input some primitive integer data and all the logic and arithmetic operations we perform on that integer are O(1) (no loops over the bits), the problem can be solved in constant time. Of course, if we changed from 32bit integer to 64bit integer the running time would increase as the arithmetic operations would take longer on hardware.
One possible solution is to use following functions. The first gives you a number where only the lowest set bit of x is set
int lowestBitSet(int x){
( x & ~(x-1) )
}
and the second the lowest bit not set
int lowestBitNotSet(int x){
return ~x & (x+1);
}
If you work few examples of these on paper you see how they work.
Now you can find the bits you need to change using these two functions and then use the algorithm you already described.
A c++ implementation (not checking for cases where there are no answer)
unsigned int closestInt(unsigned int x){
unsigned int ns=lowestBitNotSet(x);
unsigned int s=lowestBitSet(x);
if (ns>s){
x|=ns;
x^=ns>>1;
}
else{
x^=s;
x|=s>>1;
}
return x;
}
To solve this problem in O(1) time complexity it can be considered that there are two main cases:
1) When LSB is '0':
In this case, the first '1' must be shifted with one position to the right.
Input : "10001000"
Out ::: "10000100"
2) When LSB is '1':
In this case the first '0' must be set to '1', and first '1' must be set to '0'.
Input : "10000111"
Out ::: "10001110"
The next method in Java represents one solution.
private static void findClosestInteger(String word) { // ex: word = "10001000"
System.out.println(word); // Print initial binary format of the number
int x = Integer.parseInt(word, 2); // Convert String to int
if((x & 1) == 0) { // Evaluates LSB value
// Case when LSB = '0':
// Input: x = 10001000
int firstOne = x & ~(x -1); // get first '1' position (from right to left)
// firstOne = 00001000
x = x & (x - 1); // set first '1' to '0'
// x = 10000000
x = x | (firstOne >> 1); // "shift" first '1' with one position to right
// x = 10000100
} else {
// Case when LSB = '1':
// Input: x = 10000111
int firstZero = ~x & ~(~x - 1); // get first '0' position (from right to left)
// firstZero = 00001000
x = x & (~1); // set first '1', which is the LSB, to '0'
// x = 10000110
x = x | firstZero; // set first '0' to '1'
// x = 10001110
}
for(int i = word.length() - 1; i > -1 ; i--) { // print the closest integer with same weight
System.out.print("" + ( ( (x & 1 << i) != 0) ? 1 : 0) );
}
}
The problem can be viewed as "which differing bits to swap in a bit representation of a number, so that the resultant number is closest to the original?"
So, if we we're to swap bits at indices k1 & k2, with k2 > k1, the difference between the numbers would be 2^k2 - 2^k1. Our goal is to minimize this difference. Assuming that the bit representation is not all 0s or all 1s, a simple observation yields that the difference would be least if we kept |k2 - k1| as minimum. The minimum value can be 1. So, if we're able to find two consecutive different bits, starting from the least significant bit (index = 0), our job is done.
The case where bits starting from Least Significant Bit to the right most set bit are all 1s
k2
|
7 6 5 4 3 2 1 0
---------------
n: 1 1 1 0 1 0 1 1
rightmostSetBit: 0 0 0 0 0 0 0 1
rightmostNotSetBit: 0 0 0 0 0 1 0 0 rightmostNotSetBit > rightmostSetBit so,
difference: 0 0 0 0 0 0 1 0 i.e. rightmostNotSetBit - (rightmostNotSetBit >> 1):
---------------
n + difference: 1 1 1 0 1 1 0 1
The case where bits starting from Least Significant Bit to the right most set bit are all 0s
k2
|
7 6 5 4 3 2 1 0
---------------
n: 1 1 1 0 1 1 0 0
rightmostSetBit: 0 0 0 0 0 1 0 0
rightmostNotSetBit: 0 0 0 0 0 0 0 1 rightmostSetBit > rightmostNotSetBit so,
difference: 0 0 0 0 0 0 1 0 i.e. rightmostSetBit -(rightmostSetBit>> 1)
---------------
n - difference: 1 1 1 0 1 0 1 0
The edge case, of course the situation where we have all 0s or all 1s.
public static long closestToWeight(long n){
if(n <= 0 /* If all 0s */ || (n+1) == Integer.MIN_VALUE /* n is MAX_INT */)
return -1;
long neg = ~n;
long rightmostSetBit = n&~(n-1);
long rightmostNotSetBit = neg&~(neg-1);
if(rightmostNotSetBit > rightmostSetBit){
return (n + (rightmostNotSetBit - (rightmostNotSetBit >> 1)));
}
return (n - (rightmostSetBit - (rightmostSetBit >> 1)));
}
Attempted the problem in Python. Can be viewed as a translation of Ari's solution with the edge case handled:
def closest_int_same_bit_count(x):
# if all bits of x are 0 or 1, there can't be an answer
if x & sys.maxsize in {sys.maxsize, 0}:
raise ValueError("All bits are 0 or 1")
rightmost_set_bit = x & ~(x - 1)
next_un_set_bit = ~x & (x + 1)
if next_un_set_bit > rightmost_set_bit:
# 0 shifted to the right e.g 0111 -> 1011
x ^= next_un_set_bit | next_un_set_bit >> 1
else:
# 1 shifted to the right 1000 -> 0100
x ^= rightmost_set_bit | rightmost_set_bit >> 1
return x
Similarly jigsawmnc's solution is provided below:
def closest_int_same_bit_count(x):
# if all bits of x are 0 or 1, there can't be an answer
if x & sys.maxsize in {sys.maxsize, 0}:
raise ValueError("All bits are 0 or 1")
rightmost_set_bit = x & ~(x - 1)
next_un_set_bit = ~x & (x + 1)
if next_un_set_bit > rightmost_set_bit:
# 0 shifted to the right e.g 0111 -> 1011
x += next_un_set_bit - (next_un_set_bit >> 1)
else:
# 1 shifted to the right 1000 -> 0100
x -= rightmost_set_bit - (rightmost_set_bit >> 1)
return x
Java Solution:
//Swap the two rightmost consecutive bits that are different
for (int i = 0; i < 64; i++) {
if ((((x >> i) & 1) ^ ((x >> (i+1)) & 1)) == 1) {
// then swap them or flip their bits
int mask = (1 << i) | (1 << i + 1);
x = x ^ mask;
System.out.println("x = " + x);
return;
}
}
static void findClosestIntWithSameWeight(uint x)
{
uint xWithfirstBitSettoZero = x & (x - 1);
uint xWithOnlyfirstbitSet = x & ~(x - 1);
uint xWithNextTofirstBitSet = xWithOnlyfirstbitSet >> 1;
uint closestWeightNum = xWithfirstBitSettoZero | xWithNextTofirstBitSet;
Console.WriteLine("Closet Weight for {0} is {1}", x, closestWeightNum);
}
Code in python:
def closest_int_same_bit_count(x):
if (x & 1) != ((x >> 1) & 1):
return x ^ 0x3
diff = x ^ (x >> 1)
rbs = diff & ~(diff - 1)
i = int(math.log(rbs, 2))
return x ^ (1 << i | 1 << i + 1)
A great explanation of this problem can be found on question 4.4 in EPI.
(Elements of Programming Interviews)
Another place would be this link on geeksforgeeks.org if you don't own the book.
(Time complexity may be wrong on this link)
Two things you should keep in mind here is (Hint if you're trying to solve this for yourself):
You can use x & (x - 1) to clear the lowest set-bit (not to get confused with LSB - least significant bit)
You can use x & ~(x - 1) to get/extract the lowest set bit
If you know the O(n) solution you know that we need to find the index of the first bit that differs from LSB.
If you don't know what the LBS is:
0000 0000
^ // it's bit all the way to the right of a binary string.
Take the base two number 1011 1000 (184 in decimal)
The first bit that differs from LSB:
1011 1000
^ // this one
We'll record this as K1 = 0000 1000
Then we need to swap it with the very next bit to the right:
0000 1000
^ // this one
We'll record this as K2 = 0000 0100
Bitwise OR K1 and K2 together and you'll get a mask
mask = K1 | k2 // 0000 1000 | 0000 0100 -> 0000 1100
Bitwise XOR the mask with the original number and you'll have the correct output/swap
number ^ mask // 1011 1000 ^ 0000 1100 -> 1011 0100
Now before we pull everything together we have to consider that fact that the LSB could be 0001, and so could a bunch of bits after that 1000 1111. So we have to deal with the two cases of the first bit that differs from the LSB; it may be a 1 or 0.
First we have a conditional that test the LSB to be 1 or 0: x & 1
IF 1 return x XORed with the return of a helper function
This helper function has a second argument which its value depends on whether the condition is true or not. func(x, 0xFFFFFFFF) // if true // 0xFFFFFFFF 64 bit word with all bits set to 1
Otherwise we'll skip the if statement and return a similar expression but with a different value provided to the second argument.
return x XORed with func(x, 0x00000000) // 64 bit word with all bits set to 0. You could alternatively just pass 0 but I did this for consistency
Our helper function returns a mask that we are going to XOR with the original number to get our output.
It takes two arguments, our original number and a mask, used in this expression:
(x ^ mask) & ~((x ^ mask) - 1)
which gives us a new number with the bit at index K1 always set to 1.
It then shifts that bit 1 to the right (i.e index K2) then ORs it with itself to create our final mask
0000 1000 >> 1 -> 0000 0100 | 0001 0000 -> 0000 1100
This all implemented in C++ looks like:
unsigned long long int closestIntSameBitCount(unsigned long long int n)
{
if (n & 1)
return n ^= getSwapMask(n, 0xFFFFFFFF);
return n ^= getSwapMask(n, 0x00000000);
}
// Helper function
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask)
{
unsigned long long int swapBitMask = (n ^ mask) & ~((n ^ mask) - 1);
return swapBitMask | (swapBitMask >> 1);
}
Keep note of the expression (x ^ mask) & ~((x ^ mask) - 1)
I'll now run through this code with my example 1011 1000:
// start of closestIntSameBitCount
if (0) // 1011 1000 & 1 -> 0000 0000
// start of getSwapMask
getSwapMask(1011 1000, 0x00000000)
swapBitMask = (x ^ mask) & ~1011 0111 // ((x ^ mask) - 1) = 1011 1000 ^ .... 0000 0000 -> 1011 1000 - 1 -> 1011 0111
swapBitMask = (x ^ mask) & 0100 1000 // ~1011 0111 -> 0100 1000
swapBitMask = 1011 1000 & 0100 1000 // (x ^ mask) = 1011 1000 ^ .... 0000 0000 -> 1011 1000
swapBitMask = 0000 1000 // 1011 1000 & 0100 1000 -> 0000 1000
return swapBitMask | 0000 0100 // (swapBitMask >> 1) = 0000 1000 >> 1 -> 0000 0100
return 0000 1100 // 0000 1000 | 0000 0100 -> 0000 11000
// end of getSwapMask
return 1011 0100 // 1011 1000 ^ 0000 11000 -> 1011 0100
// end of closestIntSameBitCount
Here is a full running example if you would like compile and run it your self:
#include <iostream>
#include <stdio.h>
#include <bitset>
unsigned long long int closestIntSameBitCount(unsigned long long int n);
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask);
int main()
{
unsigned long long int number;
printf("Pick a number: ");
std::cin >> number;
std::bitset<64> a(number);
std::bitset<64> b(closestIntSameBitCount(number));
std::cout << a
<< "\n"
<< b
<< std::endl;
}
unsigned long long int closestIntSameBitCount(unsigned long long int n)
{
if (n & 1)
return n ^= getSwapMask(n, 0xFFFFFFFF);
return n ^= getSwapMask(n, 0x00000000);
}
// Helper function
unsigned long long int getSwapMask(unsigned long long int n, unsigned long long int mask)
{
unsigned long long int swapBitMask = (n ^ mask) & ~((n ^ mask) - 1);
return swapBitMask | (swapBitMask >> 1);
}
This was my solution to the problem. I guess #jigsawmnc explains pretty well why we need to have |k2 -k1| to a minimum. So in order to find the closest integer, with the same weight, we would want to find the location where consecutive bits are flipped and then flip them again to get the answer. In order to do that we can shift the number 1 unit. Take the XOR with the same number. This will set bits at all locations where there is a flip. Find the least significant bit for the XOR. This will give you the smallest location to flip. Create a mask for the location and next bit. Take an XOR and that should be the answer. This won't work, if the digits are all 0 or all 1
Here is the code for it.
def variant_closest_int(x: int) -> int:
if x == 0 or ~x == 0:
raise ValueError('All bits are 0 or 1')
x_ = x >> 1
lsb = x ^ x_
mask_ = lsb & ~(lsb - 1)
mask = mask_ | (mask_ << 1)
return x ^ mask
My solution, takes advantage of the parity of the integer. I think the way I got the LSB masks can be simplified
def next_weighted_int(x):
if x % 2 == 0:
lsb_mask = ( ((x - 1) ^ x) >> 1 ) + 1 # Gets a mask for the first 1
x ^= lsb_mask
x |= (lsb_mask >> 1)
return x
lsb_mask = ((x ^ (x + 1)) >> 1 ) + 1 # Gets a mask for the first 0
x |= lsb_mask
x ^= (lsb_mask >> 1)
return x
Just sharing my python solution for this problem:
def same closest_int_same_bit_count(a):
x = a + (a & 1) # change last bit to 0
bit = (x & ~(x-1)) # get last set bit
return a ^ (bit | bit >> 1) # swap set bit with unset bit
func findClosestIntegerWithTheSameWeight2(x int) int {
rightMost0 := ^x & (x + 1)
rightMost1 := x & (-x)
if rightMost0 > 1 {
return (x ^ rightMost0) ^ (rightMost0 >> 1)
} else {
return (x ^ rightMost1) ^ (rightMost1 >> 1)
}
}
I'm currently looking for on how to determine the CRC produced from the machine to PC (and vice-versa).
The devices are communicating using serial communication or RS232 cable.
I do only have data to be able for us to create a program to be used for both devices.
The data given was from my boss and the program was corrupted. So we are trying for it to work out.
I hope everyone can help.
Thanks :)
The sequence to use for the CRC calculation in your protocol is the ASCII string
starting from the first printing character (e.g. the 'R' from REQ)
until and including the '1E' in the calculation.
It's a CRC with the following specs according to our CRC calculator
CRC:16,1021,0000,0000,No,No
which means:
CRC width: 16 bit (of course)
polynomial: 1021 HEX (truncated CRC polynomial)
init value: 0000
final Xor applied: 0000
reflectedInput: No
reflectedOutput: No`
(If 'init value' were FFFF, it would be a "16 bit width CRC as designated by CCITT").
See also the Docklight CRC glossary and the Boost CRC library on what the CRC terms mean plus sample code.
What I did is to write a small script that tries out the popular 16 bit CRCs on varying parts of the first simple "REQ=INI" command, and see if I end up with a sum of 4255. This failed, but instead of going a full brute force with trying all sorts of polynoms, I assumed that it was maybe just an oddball / flawed implementation of the known standards, and indeed succeeded with a variation of the CRC-CCITT.
Heres is some slow & easy C code (not table based!) to calculate all sorts of CRCs:
// Generic, not table-based CRC calculation
// Based on and credits to the following:
// CRC tester v1.3 written on 4th of February 2003 by Sven Reifegerste (zorc/reflex)
unsigned long reflect (unsigned long crc, int bitnum) {
// reflects the lower 'bitnum' bits of 'crc'
unsigned long i, j=1, crcout=0;
for (i=(unsigned long)1<<(bitnum-1); i; i>>=1) {
if (crc & i) crcout|=j;
j<<= 1;
}
return (crcout);
}
calcCRC(
const int width, const unsigned long polynominal, const unsigned long initialRemainder,
const unsigned long finalXOR, const int reflectedInput, const int reflectedOutput,
const unsigned char message[], const long startIndex, const long endIndex)
{
// Ensure the width is in range: 1-32 bits
assert(width >= 1 && width <= 32);
// some constant parameters used
const bool b_refInput = (reflectedInput > 0);
const bool b_refOutput = (reflectedOutput > 0);
const unsigned long crcmask = ((((unsigned long)1<<(width-1))-1)<<1)|1;
const unsigned long crchighbit = (unsigned long)1<<(width-1);
unsigned long j, c, bit;
unsigned long crc = initialRemainder;
for (long msgIndex = startIndex; msgIndex <= endIndex; ++msgIndex) {
c = (unsigned long)message[msgIndex];
if (b_refInput) c = reflect(c, 8);
for (j=0x80; j; j>>=1) {
bit = crc & crchighbit;
crc<<= 1;
if (c & j) bit^= crchighbit;
if (bit) crc^= polynominal;
}
}
if (b_refOutput) crc=reflect(crc, width);
crc^= finalXOR;
crc&= crcmask;
return(crc);
}
With this code and the CRCs specs listed above, I have been able to re-calculate the following three sample CRCs:
10.03.2014 22:20:57.109 [TX] - REQ=INI<CR><LF>
<RS>CRC=4255<CR><LF>
<GS>
10.03.2014 22:20:57.731 [TX] - ANS=INI<CR><LF>
STATUS=0<CR><LF>
<RS>CRC=57654<CR><LF>
<GS>
10.03.2014 22:20:59.323 [TX] - ANS=INI<CR><LF>
STATUS=0<CR><LF>
MID="CTL1"<CR><LF>
DEF="DTLREQ";1025<CR><LF>
INFO=0<CR><LF>
<RS>CRC=1683<CR><LF>
<GS>
I failed on the very complex one with the DEF= parts - probably didn't understand the character sequence correctly.
The Docklight script I used to reverse engineer this:
Sub crcReverseEngineer()
Dim crctypes(7)
crctypes(0) = "CRC:16,1021,FFFF,0000" ' CCITT
crctypes(1) = "CRC:16,8005,0000,0000" ' CRC-16
crctypes(2) = "CRC:16,8005,FFFF,0000" ' CRC-MODBUS
' lets try also some nonstandard variations with different init and final Xor, but stick
' to the known two polynoms.
crctypes(3) = "CRC:16,1021,FFFF,FFFF"
crctypes(4) = "CRC:16,1021,0000,FFFF"
crctypes(5) = "CRC:16,1021,0000,0000"
crctypes(6) = "CRC:16,8005,FFFF,FFFF"
crctypes(7) = "CRC:16,8005,FFFF,0000"
crcString = "06 1C 52 45 51 3D 49 4E 49 0D 0A 1E 43 52 43 3D 30 30 30 30 0D 0A 1D"
For reflectedInOrOut = 0 To 3
For cType = 0 To 7
crcSpec = crctypes(cType) & "," & IIf(reflectedInOrOut Mod 2 = 1, "Yes", "No") & "," & IIf(reflectedInOrOut > 1, "Yes", "No")
For cStart = 1 To 3
For cEnd = 9 To (Len(crcString) + 1) / 3
subDataString = Mid(crcString, (cStart - 1) * 3 + 1, (cEnd - cStart + 1) * 3)
result = DL.CalcChecksum(crcSpec, subDataString, "H")
resultInt = CLng("&h" + Left(result, 2)) * 256 + CLng("&h" + Right(result, 2))
If resultInt = 4255 Then
DL.AddComment "Found it!"
DL.AddComment "sequence: " & subDataString
DL.AddComment "CRC spec: " & crcSpec
DL.AddComment "CRC result: " & result & " (Integer = " & resultInt & ")"
Exit Sub
End If
Next
Next
Next
Next
End Sub
Public Function IIf(blnExpression, vTrueResult, vFalseResult)
If blnExpression Then
IIf = vTrueResult
Else
IIf = vFalseResult
End If
End Function
Hope this helps and I'm happy to provide extra information or clarify details.
I’ve got my hands on a 16-bit rgb565 image (specifically, an Android framebuffer dump), and I would like to convert it to 24-bit rgb888 for viewing on a normal monitor.
The question is, how does one convert a 5- or 6-bit channel to 8 bits? The obvious answer is to shift it. I started out by writing this:
puts("P6 320 480 255");
uint16_t buf;
while (read(0, &buf, sizeof buf)) {
unsigned char red = (buf & 0xf800) >> 11;
unsigned char green = (buf & 0x07e0) >> 5;
unsigned char blue = buf & 0x001f;
putchar(red << 3);
putchar(green << 2);
putchar(blue << 3);
}
However, this doesn’t have one property I would like, which is for 0xffff to map to 0xffffff, instead of 0xf8fcf8. I need to expand the value in some way, but I’m not sure how that should work.
The Android SDK comes with a tool called ddms (Dalvik Debug Monitor) that takes screen captures. As far as I can tell from reading the code, it implements the same logic; yet its screenshots are coming out different, and white is mapping to white.
Here’s the raw framebuffer, the smart conversion by ddms, and the dumb conversion by the above algorithm. Note that the latter is slightly darker and greener.
(By the way, this conversion is implemented in ffmpeg, but it’s just performing the dumb conversion listed above, leaving the LSBs at all zero.)
I guess I have two questions:
What’s the most sensible way to convert rgb565 to rgb888?
How is DDMS converting its screenshots?
You want to map each of these from a 5/6 bit space to an 8 bit space.
5 bits = 32 values
6 bits = 64 values
8 bits = 256 values
The code you're using is taking the naive approach that x5 * 256/32 = x8 where 256/32 = 8 and multiplying by 8 is left shift 3 but, as you say, this doesn't necessarily fill the new number space "correctly". 5 to 8 for max value is 31 to 255 and therein lies your clue to the solution.
x8 = 255/31 * x5
x8 = 255/63 * x6
where x5, x6 and x8 are 5, 6 and 8 bit values respectively.
Now there is a question about the best way to implement this. It does involve division and with integer division you will lose any remainder result (round down basically) so the best solution is probably to do floating point arithmetic and then round half up back to an integer.
This can be sped up considerably by simply using this formula to generate a lookup table for each of the 5 and 6 bit conversions.
My few cents:
If you care about precise mapping, yet fast algorithm you can consider this:
R8 = ( R5 * 527 + 23 ) >> 6;
G8 = ( G6 * 259 + 33 ) >> 6;
B8 = ( B5 * 527 + 23 ) >> 6;
It uses only: MUL, ADD and SHR -> so it is pretty fast!
From the other side it is compatible in 100% to floating point mapping with proper rounding:
// R8 = (int) floor( R5 * 255.0 / 31.0 + 0.5);
// G8 = (int) floor( G6 * 255.0 / 63.0 + 0.5);
// B8 = (int) floor( R5 * 255.0 / 31.0 + 0.5);
Some extra cents:
If you are interested in 888 to 565 conversion, this works very well too:
R5 = ( R8 * 249 + 1014 ) >> 11;
G6 = ( G8 * 253 + 505 ) >> 10;
B5 = ( B8 * 249 + 1014 ) >> 11;
Constants were found using brute force search with somę early rejections to speed thing up a bit.
You could shift and then or with the most significant bits; i.e.
Red 10101 becomes 10101000 | 101 => 10101101
12345 12345--- 123 12345123
This has the property you seek, but it's not the most linear mapping of values from one space to the other. It's fast, though. :)
Cletus' answer is more complete and probably better. :)
iOS vImage Conversion
The iOS Accelerate Framework documents the following algorithm for the vImageConvert_RGB565toARGB8888 function:
Pixel8 alpha = alpha
Pixel8 red = (5bitRedChannel * 255 + 15) / 31
Pixel8 green = (6bitGreenChannel * 255 + 31) / 63
Pixel8 blue = (5bitBlueChannel * 255 + 15) / 31
For a one-off conversion this will be fast enough, but if you want to process many frames you want to use something like the iOS vImage conversion or implement this yourself using NEON intrinsics.
From ARMs Community Forum Tutorial
First, we will look at converting RGB565 to RGB888. We assume there are eight 16-bit pixels in register q0, and we would like to separate reds, greens and blues into 8-bit elements across three registers d2 to d4.
vshr.u8 q1, q0, #3 # shift red elements right by three bits,
# discarding the green bits at the bottom of
# the red 8-bit elements.
vshrn.i16 d2, q1, #5 # shift red elements right and narrow,
# discarding the blue and green bits.
vshrn.i16 d3, q0, #5 # shift green elements right and narrow,
# discarding the blue bits and some red bits
# due to narrowing.
vshl.i8 d3, d3, #2 # shift green elements left, discarding the
# remaining red bits, and placing green bits
# in the correct place.
vshl.i16 q0, q0, #3 # shift blue elements left to most-significant
# bits of 8-bit color channel.
vmovn.i16 d4, q0 # remove remaining red and green bits by
# narrowing to 8 bits.
The effects of each instruction are described in the comments above, but in summary, the operation performed on each channel is:
Remove color data for adjacent channels using shifts to push the bits off either end of the element.
Use a second shift to position the color data in the most-significant bits of each element, and narrow to reduce element size from 16 to eight bits.
Note the use of element sizes in this sequence to address 8 and 16 bit elements, in order to achieve some of the masking operations.
A small problem
You may notice that, if you use the code above to convert to RGB888 format, your whites aren't quite white. This is because, for each channel, the lowest two or three bits are zero, rather than one; a white represented in RGB565 as (0x1F, 0x3F, 0x1F) becomes (0xF8, 0xFC, 0xF8) in RGB888. This can be fixed using shift with insert to place some of the most-significant bits into the lower bits.
For an Android specific example I found a YUV-to-RGB conversion written in intrinsics.
Try this:
red5 = (buf & 0xF800) >> 11;
red8 = (red5 << 3) | (red5 >> 2);
This will map all zeros into all zeros, all 1's into all 1's, and everything in between into everything in between. You can make it more efficient by shifting the bits into place in one step:
redmask = (buf & 0xF800);
rgb888 = (redmask << 8) | ((redmask<<3)&0x070000) | /* green, blue */
Do likewise for green and blue (for 6 bits, shift left 2 and right 4 respectively in the top method).
The general solution is to treat the numbers as binary fractions - thus, the 6 bit number 63/63 is the same as the 8 bit number 255/255. You can calculate this using floating point math initially, then compute a lookup table, as other posters suggest. This also has the advantage of being more intuitive than bit-bashing solutions. :)
There is an error jleedev !!!
unsigned char green = (buf & 0x07c0) >> 5;
unsigned char blue = buf & 0x003f;
the good code
unsigned char green = (buf & 0x07e0) >> 5;
unsigned char blue = buf & 0x001f;
Cheers,
Andy
I used the following and got good results. Turned out my Logitek cam was 16bit RGB555 and using the following to convert to 24bit RGB888 allowed me to save as a jpeg using the smaller animals ijg: Thanks for the hint found here on stackoverflow.
// Convert a 16 bit inbuf array to a 24 bit outbuf array
BOOL JpegFile::ByteConvert(BYTE* inbuf, BYTE* outbuf, UINT width, UINT height)
{ UINT row_cnt, pix_cnt;
ULONG off1 = 0, off2 = 0;
BYTE tbi1, tbi2, R5, G5, B5, R8, G8, B8;
if (inbuf==NULL)
return FALSE;
for (row_cnt = 0; row_cnt <= height; row_cnt++)
{ off1 = row_cnt * width * 2;
off2 = row_cnt * width * 3;
for(pix_cnt=0; pix_cnt < width; pix_cnt++)
{ tbi1 = inbuf[off1 + (pix_cnt * 2)];
tbi2 = inbuf[off1 + (pix_cnt * 2) + 1];
B5 = tbi1 & 0x1F;
G5 = (((tbi1 & 0xE0) >> 5) | ((tbi2 & 0x03) << 3)) & 0x1F;
R5 = (tbi2 >> 2) & 0x1F;
R8 = ( R5 * 527 + 23 ) >> 6;
G8 = ( G5 * 527 + 23 ) >> 6;
B8 = ( B5 * 527 + 23 ) >> 6;
outbuf[off2 + (pix_cnt * 3)] = R8;
outbuf[off2 + (pix_cnt * 3) + 1] = G8;
outbuf[off2 + (pix_cnt * 3) + 2] = B8;
}
}
return TRUE;
}
Here's the code:
namespace convert565888
{
inline uvec4_t const _c0{ { { 527u, 259u, 527u, 1u } } };
inline uvec4_t const _c1{ { { 23u, 33u, 23u, 0u } } };
} // end ns
uvec4_v const __vectorcall rgb565_to_888(uvec4_v const rgba) {
return(uvec4_v(_mm_srli_epi32(_mm_add_epi32(_mm_mullo_epi32(rgba.v,
uvec4_v(convert565888::_c0).v), uvec4_v(convert565888::_c1).v), 6)));
}
and for rgb 888 to 565 conversion:
namespace convert888565
{
inline uvec4_t const _c0{ { { 249u, 509u, 249u, 1u } } };
inline uvec4_t const _c1{ { { 1014u, 253u, 1014u, 0u } } };
} // end ns
uvec4_v const __vectorcall rgb888_to_565(uvec4_v const rgba) {
return(uvec4_v(_mm_srli_epi32(_mm_add_epi32(_mm_mullo_epi32(rgba.v,
uvec4_v(convert888565::_c0).v), uvec4_v(convert888565::_c1).v), 11)));
}
for the explanation of where all these numbers come from, specifically how I calculated the optimal multiplier and bias for green:
Desmos graph -
https://www.desmos.com/calculator/3grykboay1
The graph isn't the greatest but it shows the actual value vs. error -- play around with the interactive sliders to see how different values affect the output. This graph also applies to calculating the red and blue values aswell. Typically green is shifted by 10bits, red and blue 11bits.
In order for this to work with intrinsic _mm_srli_epi32 / _mm_srl_epi32 requires all components to be shifted by the same amount. So everything is shifted by 11 bits (rgb888_to_565) in this version, however, the green component is scaled to compensate for this change. Fortunately, it scales perfectly!
I had this difficulty too, and the most faithful way I found was to replace the 16-bit value with the original 24-bit value. Now the ILI9341 screen color is visually compatible with Notebook screen. I thought of just using the 24-bit color table, but then the display routines would have to be converted to 565, and that would make the program even slower.
If the color palette is fixed as in my case, it might be the most viable option. I tried to make use of the 3 MSB adding with the 3 LSB, but it wasn't very good.
The colors I used on the ILI9341 display I got from this website (Note: I choose the 24-bit color 888 and get the 16-bit color 565, on this website there's no way to do otherwise):
http://www.barth-dev.de/online/rgb565-color-picker/
For example, I read the pixel color of the ILI9341 display and save it to a USB Disk, in a file, in BMP format. As the display operates with 16-bit or 18-bit, I have no way to retrieve 24-bit information directly from the GRAM memory.
#define BLACK_565 0x0000
#define BLUE_565 0x001F
#define RED_565 0xF800
#define GREEN_565 0x07E0
#define CYAN_565 0x07FF
#define MAGENTA_565 0xF81F
#define YELLOW_565 0xFFE0
#define WHITE_565 0xFFFF
#define LIGHTGREY_565 0xC618
#define ORANGE_565 0xFD20
#define GREY_565 0x8410
#define DARKGREY_565 0x2104
#define DARKBLUE_565 0x0010
#define DARKGREEN_565 0x03E0
#define DARKCYAN_565 0x03EF
#define DARKYELLOW_565 0x8C40
#define BLUESKY_565 0x047F
#define BROWN_565 0xC408
#define BLACK_888 0x000000
#define BLUE_888 0x0000FF
#define RED_888 0xFF0000
#define GREEN_888 0x04FF00
#define CYAN_888 0x00FFFB
#define MAGENTA_888 0xFF00FA
#define YELLOW_888 0xFBFF00
#define WHITE_888 0xFFFFFF
#define LIGHTGREY_888 0xC6C3C6
#define ORANGE_888 0xFFA500
#define GREY_888 0x808080
#define DARKGREY_888 0x202020
#define DARKBLUE_888 0x000080
#define DARKGREEN_888 0x007D00
#define DARKCYAN_888 0x007D7B
#define DARKYELLOW_888 0x898A00
#define BLUESKY_888 0x008CFF
#define BROWN_888 0xC08240
I did the test (using an STM32F407 uC) with an IF statement, but it can also be done with Select Case, or another form of comparison.
uint16_t buff1; // pixel color value read from GRAM
uint8_t buff2[3];
uint32_t color_buff; // to save to USB disk
if (buff1 == BLUE_565) color_buff = BLUE_888;
else if (buff1 == RED_565) color_buff = RED_888;
else if (buff1 == GREEN_565) color_buff = GREEN_888;
else if (buff1 == CYAN_565) color_buff = CYAN_888;
else if (buff1 == MAGENTA_565) color_buff = MAGENTA_888;
else if (buff1 == YELLOW_565) color_buff = YELLOW_888;
else if (buff1 == WHITE_565) color_buff = WHITE_888;
else if (buff1 == LIGHTGREY_565) color_buff = LIGHTGREY_888;
else if (buff1 == ORANGE_565) color_buff = ORANGE_888;
else if (buff1 == GREY_565) color_buff = GREY_888;
else if (buff1 == DARKGREY_565) color_buff = DARKGREY_888;
else if (buff1 == DARKBLUE_565) color_buff = DARKBLUE_888;
else if (buff1 == DARKCYAN_565) color_buff = DARKCYAN_888;
else if (buff1 == DARKYELLOW_565) color_buff = DARKYELLOW_888;
else if (buff1 == BLUESKY_565) color_buff = BLUESKY_888;
else if (buff1 == BROWN_565) color_buff = BROWN_888;
else color_buff = BLACK;
RGB separation for saving to 8-bit variables:
buff2[0] = color_buff; // Blue
buff2[1] = color_buff >> 8; // Green
buff2[2] = color_buff >> 16; // Red