Image Preservation using Wavelet Based On Kronecker Mask, Birge - Massart And Parity Strategy

Abstract

Image carries more information about the ideas than text. Growth of social media, images has become the universal language because it is more interactive. Images are used in different fields like medical, multimedia, industries etc. When using the images, we need to find effective storage and transmission methods to reduce storage size and transmission time. Lossless and lossy are two ways to compress the image to reduce the storage and transmission time. The proposed method implements the concept of lossless image compression using the method of Kronecker delta notation, wavelet based on Birge-Massart strategy and parity strategy. This paper presents that enhancing the image by applying the Kronecker delta notation as the mask and applying the wavelet based on Birge-Massart strategy, finally applying the parity threshold to compress the image. The proposed method is compared the compression ratio (CR) with the existing lossless compression methods such as Birge – Massart without the enhanced method and Unimodal method. This proposed algorithm is very simple and more efficient to reduce the storage capacity and maintain the quality of an image than the existing lossless compression techniques. The experimental result shows that the Birge-Massart strategy combined with Kronecker mask and parity threshold produces the best CR than the simple Birge- Massart(without enhancement and threshold) strategy. This efficient method is proved by without loss of information of an original image with low MSE, high PSNR and high CR. An experimental result shows that the proposed algorithm achieved maximum CR of 146% on medical images and maximum CR of 19.2% on standard images than the existing methods.

Subband Thresholding for Near-Lossless Medical Image Compression

“…Their technique achieves better performance outputs regarding PSNR when compared with different RLE methods and JPEG. A lossless medical image compression method proposed in [13] incorporates Kronecker delta mask for preprocessing and used Brige-Massart and Parity Strategy methods based on wavelets, which includes unimodal thresholding for compression. CT, MRI and other standard images are used as test images.…”

Color Image Compression Based on Contrast Sensitivity with Quality Factor

“…The Quantization is an essential part in compression algorithm to reduce the number of bits per sample [33]. In this proposed method, quantization process concentrated on contrast sensitive value of each block.…”