Colour image compression with colour conversion and hybrid algorithm

M. Raghavendra, H. S. Prasantha, S. Sandya
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Abstract

The astounding augmentation of multimedia in the fields of communication media, medicine, surveillance etc. resulted in the huge volume of data acquirement. The storage of these data requires massive memory. For communication, these data need enormous transmission bandwidth. The only solution to reduce the storage and the transmission bandwidth is the data compression. From the literature survey it is learnt that there is a need to achieve compression ratio greater than 30 with a PSNR greater than 25 dB for non critical applications. In order to facilitate this, a colour image compression method is proposed. In this method, the colour image is converted into the “YCbCr” format using formulated New Equation Set-1. The “Y” component matrix is divided into 16×16 blocks. The DCT is applied to all the 16×16 blocks. The DC-Coefficient of all 16×16 block DCT is taken out and zero is inserted in place of it. The data types of all the DC-coefficients are changed from the “double” to the “16 bit integer” data type and they are stored. The transformed matrix consists of 16×16 block DCT of all the blocks. In this matrix, all those elements less than the threshold value “th” are made zero. This matrix is decomposed into matrices “U”, “S” and “V” using SVD. All those elements of the matrix “U” less than the threshold value “thu”, all those elements of the matrix “S” less than the threshold value “ths” and all those elements of the matrix “V” less than the threshold value “thv” are made zero. Then these matrices are multiplied to form one matrix such that X=USVT. All those elements of the matrix “X” less than the threshold value “th” are made zero. Now all the elements of the matrix “X” are divided by 10. Then the matrix “X” becomes a sparse matrix. This sparse matrix is represented in the “triplet form”. The data types of the “row values” and the “column values” of the triplet form are converted from the “double” to the “16 bit integer” data type. The data type of the “data elements” of the “triplet form” is converted into the “8 bit integer” data type. Then the RLE is applied to the “column values” of the “triplet form”. After this, the compressed form of the Y-Component Matrix is obtained. Similarly, the “Cb” and the “Cr” component matrices are compressed. Then the experiments are conducted by converting the given image into the “YCbCr” format by the formulated New Equation Set-2, New Equation Set-3 and the basic “YCbCr” equation. The results are compared with parameters such as Compression Ratio, PSNR, SSIM and Quality Index. Experiments are conducted using MATLAB. From the results, it can be concluded that, the compression ratio obtained from the method which has got the colour conversion using New Equation Set-1 is good. The maximum compression ratio obtained with this method is 43.5079 with a PSNR of Red, Green and Blue Component equal to 25.9583 dB, 25.7501 dB and 26.4837 dB respectively.
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彩色图像压缩的颜色转换和混合算法
多媒体在通信媒体、医疗、监控等领域的迅猛发展导致了海量的数据采集。这些数据的存储需要大量的内存。为了通信,这些数据需要巨大的传输带宽。减少存储和传输带宽的唯一解决方案是数据压缩。从文献调查中了解到,对于非关键应用,需要实现大于30的压缩比,PSNR大于25 dB。为此,提出了一种彩色图像压缩方法。在该方法中,使用新方程集1将彩色图像转换为“YCbCr”格式。“Y”分量矩阵分为16×16块。DCT应用于所有16×16块。取出所有16×16块DCT的dc系数,代之以零。所有dc系数的数据类型从“double”变为“16位整型”数据类型并存储。变换后的矩阵由16×16所有块的块DCT组成。在这个矩阵中,所有小于阈值th的元素都为零。将该矩阵用SVD分解为矩阵“U”、“S”和“V”。矩阵U中小于阈值thu的所有元素,矩阵S中小于阈值thv的所有元素以及矩阵V中小于阈值thv的所有元素均为零。然后将这些矩阵相乘形成一个矩阵,使得X=USVT。矩阵“X”中小于阈值“th”的所有元素都为零。现在矩阵X的所有元素都除以10。那么矩阵X就变成了一个稀疏矩阵。这个稀疏矩阵用“三元组形式”表示。将三元组形式的“行值”和“列值”的数据类型由“double”转换为“16位整型”数据类型。将“三元组形式”的“数据元素”的数据类型转换为“8位整数”数据类型。然后将RLE应用于“三元形式”的“列值”。然后得到y分量矩阵的压缩形式。类似地,“Cb”和“Cr”分量矩阵被压缩。然后利用新方程集2、新方程集3和基本的“YCbCr”方程,将给定图像转换成“YCbCr”格式,进行实验。结果与压缩比、PSNR、SSIM、质量指数等参数进行了比较。利用MATLAB进行了实验。结果表明,利用新方程集1进行颜色转换的方法得到的压缩比较好。该方法获得的最大压缩比为43.5079,其中红、绿、蓝分量的PSNR分别为25.9583 dB、25.7501 dB和26.4837 dB。
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