Color Image Compression using arith and walsh tran
2016-08-23
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This technique uses color image compression, a new technique between discrete mixed wavelet transform and discrete cosine transform. (a) First step; transform the image by using three-level discrete wavelet transform (b) second step; quantize and eliminate zeros to form each subband, and then compress the arithmetic coding of each subband (c) third step; compress LL3 subband 1-compress color image by using T-matrix coding implementation in MATLAB. Before writing your program, you must start from mathwork Download the following website: - & quot; arith_ Code. M & quot; - & quot; TransformDCT. M & quot; both functions use cic2011 method, you can download from here: mathwork Æ - Author - Mohammed siddeq, and then copy & quot; arith_ Code. M & quot; and & quot; TransformDCT. M & quot; & quot; cic2011 & quot; in the same folder, you can finally write your program to compress color images, in MATLAB language: Im = imread (\'c: imageimage2. BMP \ '); quantization = [0.05, 0.20.2]; data = code_ Color_ Image_ DWT_ DCT (IM, quantized, \'c: comp. CIC \ ', \'db5 \';'I & quot;: - represents the quantization value [0.01-0.5] of RGB color image from path \'c: imageimage2. BMP \ '& quot;: - in the range of each layer (r.g.b.). In the quantization step, the value between [0.01-0.05] is always used for the first layer, while for the second and third layers, more than 0.05 can be used. These factors can be used to reduce the maximum value in each layer, if the quantization value increases, the image will be damaged or degraded. For this reason, we always use small values. In order to obtain good image quality and better compression. Please refer to the following proposed quantization: - quantization = [0.01, 0.1, 0.1]
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