java,image,javax.imageio,image-compression,run-length-encoding

See this example for how to write using ImageWriter and using ImageWriteParam (use an instance of BMPImageWriteParam in your case). Scroll a bit down to find the write example. Instead of the line: ImageWriteParam param = writer.getDefaultWriteParam(); You should insert something like: BMPImageWriteParam param = new BMPImageWriteParam(); param.setCompressionMode(ImageWriteParam.MODE_EXPLICIT); param.setCompressionType("BI_RLE8"); You...

This should do the trick: y = diff(find(diff([nan ; x(:) ; nan]) ~= 1)) The inner diff looks for steps that are not +1 (sequence breaks), the find determines the corresponding positions (indices), the outer diff computes sequence lengths as differences between sequence break positions. The nans are there to...

compression,mp3,wav,run-length-encoding

No, neither codec can do this. WAV files (typically) use PCM, which holds a value for every single sample. Even if there were complete digital silence (all values the same), every sample is stored. MP3 works in frames of 1,152 samples. Each frame stands alone (well, there is the bit...

arrays,matlab,run-length-encoding

You could use an existing code for run-length-encoding, which does the (ugly) work for you and then filter out your vectors yourself. This way your helper function is rather general and its functionality is evident from the name runLengthEncode. Reusing code from this answer: function [lengths, values] = runLengthEncode(data) startPos...

database,algorithm,run-length-encoding,bitmap-index

By the nature of the bitmap index the number of 1s in the whole matrix will not exceed N (and will equal N if columns for all the values are in place). The compressed size of a column with N[i] 1s will be O(N[i]) (with the worst case being 1s...

performance,matlab,run-length-encoding

To find out which one is the most efficient solution, we provide a test-script that evaluates the performance. The first plot depicts runtimes for growing length of the vector runLengths, where the entries are uniformly distributed with maximum length 200. A modification of gnovice's solution is the fastest, with Divakar's...

Here is the working source code: // Chapter 22 Programming Project #7 #include <stdio.h> #include <string.h> #include <stdlib.h> #include <ctype.h> void compress_file(FILE *fp_in, FILE *fp_out); void uncompress_file(FILE *fp_in, FILE *fp_out); int main(void) { FILE *fp_in, *fp_out; char nm_in[FILENAME_MAX], nm_out[FILENAME_MAX]; int chk; for (;;) { printf(" ----------------------------------------- \n"); printf("| 1 -...

This should do the trick: RunLengthCoding = [77 -6 -11 -18 -6 -6 2 -1 4 -1 -1 6 3 1 -1 0 0 0 2 1 2 -1 -1 0 -1 1 0 0 0 0 0 0 -1 0 0 1 0 0 0 0 0 0 0...

compression,huffman-coding,run-length-encoding

If RLE works, Huffman will work all the better. There's a proof that if your file is large enough, Huffman will converge to the maximum possible entropy, thus maximizing compression.

There should be better way I suppose, but this should work Using cumsum,diff,accumarray & bsxfun %// doing the 'diff' along default dim to get the adjacent equality out = [ones(1,size(A,2));diff(A)]; %// Putting all other elements other than zero to 1 out(find(out)) = 1; %// getting all the indexes of 0...

java,image-processing,image-compression,run-length-encoding

You should be able to use a ByteArrayOutputStream in the exact same way you use the StringBuffer: public byte[] getRunLength(){ ByteArrayOutputStream dest = new ByteArrayOutputStream(); for(int i =0; i < imageByteArray.length; i++){ int runlength = 1; while(i+1 < imageByteArray.length && imageByteArray[i] == imageByteArray[i+1]){ runlength++; i++; } dest.write((byte)runlength); dest.write((byte)imageByteArray[i]); } return...