Title: Still Image Compression Using Lossy Source Coding By Low-Density Generator Matrix Codes
Abstract: Image and video storage and fast data transfer for different purposes increase demand to compress video and images. Compression techniques are divided into two major categories, lossy compression and lossless compression, in this article we aim to implement a lossy compression method for this purpose, first we use discrete cosine transform (DCT) to obtain fundamental frequency components, then we use a binary quantizer by Low Density Generator Matrix (LDGM) coding and after that the quantized data will be compressed efficiently with Lempel-Ziv-Welch (LZW) method that is a method of lossless compression. The proposed algorithm has been compared with JPEG and JPEG2000, using several standard test images. The experimental results confirm that the proposed algorithm has higher performance in term of the PSNR and SSIM values. The PSNR at compression ratio of 20:1 for Bridge test image is 27.96 dB for the proposed technique which is 2.47 dB higher than JPEG technique.
Publication Year: 2016
Publication Date: 2016-01-01
Language: en
Type: dissertation
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot