{"title":"Colour image compression with colour conversion and hybrid algorithm","authors":"M. Raghavendra, H. S. Prasantha, S. Sandya","doi":"10.1109/ICNETS2.2017.8067898","DOIUrl":null,"url":null,"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=USV<sup>T</sup>. 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.","PeriodicalId":413865,"journal":{"name":"2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNETS2.2017.8067898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.