Comparative analysis of variable quantization DCT and variable rank matrix SVD algorithms for image compression applications

Compressing an image is significantly different than compressing raw binary data. Evidently, general purpose compression algorithms can be used to compress images, but the result is less than optimal. Discrete Cosine Transform (DCT) has been widely used in signal processing of image. Joint Photographic Experts Group (JPEG) is a commonly used standard technique of compression for photographic images and in turn utilizes DCT. Apart from DCT, their also exist a decomposition algorithm well known as Singular Value Decomposition (SVD). The proposed schemes investigate the performance evaluation of variable quantization DCT and variable rank of image matrix SVD based image compression. The numerical analysis of such algorithms is carried out by measuring Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR).