A DWT based lossless gray Image Compression

In this code, a new hybrid technique using the discrete wavelet transform (DWT) is presented. We show evaluation using the Power Signal to Noise Ratio (PSNR) as a measure of quality, we show that DWT with threshold, Quantization, and combination of RLE and Huffman as coding stage, provides a better performance than JPEG in terms of PSNR and we can get an important CR.
Our Algorithm is like that:
Reading image-->DWT transformation-->Thresholding-->Quantization-->RLE encoding--> Huffman encoding-->Save a compressed image in file (*.Hdwt)
in decompression steps we should open file(*.Hdwt) aafter that the steps will be like that: Huffman decoding-->RLE decoding--> Quantization inverse-->IDCT transformation-->Open image as Bmp image
Files:
compdwt.m:
main code to compress an image we only run compdct.m
decompdwt.m:
To reconstruct our image we mean here if we want to decompress the file obtained before (.Hdwt) only we run this code and chose the file interested.
resize.m:
proba.m: frequency calculation.
rle.m: Run length encoding
irle.m: Inverse Run length encoding
abais.m: reduce value big than 255