Paper Title :Analyzing Lossless Patch Wise Code Formation in Image Compression

Author :V.P. Kulalvaimozhi, M. Germanus Alex, S. John Peter

Article Citation :V.P. Kulalvaimozhi ,M. Germanus Alex ,S. John Peter , (2019 ) " Analyzing Lossless Patch Wise Code Formation in Image Compression " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 19-25, Volume-7, Issue-4

Abstract : Image compression is more important for the efficient data transfer of the data and to maintain the secrecy of the data that is to be transmitted. The main problem that is faced in the compression is the effective decompression. The input images that is compressed may not be more effectively restored in the compression process based on quantization using Cosine Transformations or Wavelet transformations. While using transformations the pixel information were lost. To overcome these process encoding process were employed. In the encoding process the pixel information were well preserved but the compression efficiency is not improved. Inorder to overcome this problem Lossless Patch Wise Code Formation (LPWCF) is employed. In the patch wise code generation the compression process is based on the pixel grouping and removing the relevant and recurrent pixels. In the proposed method the images were first reduced in size by combining the current pixel with the previous pixel. The resulting image size is nearly the half of the size of the input image. The resulting image is then divided into small patches. In the patch recurrent pixels and their locations were identified. The identified pixel locations were placed previous to the pixel value and the process is repeated for the complete image. The result of the each patch acts as the code. In the receiver side the same process is reversed inorder to obtain the decompressed image. The process is completely reversible and hence the process can be employed in the transmission of the images. The per formance of the process is measured in terms of the compression ratio and the image quality analysis of the input and the decompressed image based on PSNR, MSE and SSIM. Keywords - Compression, Pixel Grouping, Recurrent Pixels, bits per pixel per band (bpppb), Decompression.

Type : Research paper

Published : Volume-7, Issue-4

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