Enhanced SVD Based Image Compression Technique
With the growth of technology and entrance into the Digital World, it has found itself surrounded by a massive quantity of data. Dealing with such huge data/information will often creates difficulties while transmission of data or storage of data. One feasible solution to overcome such difficulties is to use a data compression technique. Image compression is a method in which the storage space or processing space of image is reduced without degrading the image standard or quality. It conjointly reduces the time needed for images to be uploaded over the Internet or downloaded from Internet. JPEG is a necessary technique used for image compression. So, in order to improve the quality of the image, compression is done using different techniques. In this research work, SVD algorithm is used for compression which is giving better result for image compression without any reduction in quality. The modeling of optimized Singular Value Decomposition (SVD) implemented for JPEG Image compression in MATLAB is implemented. SVD is the core part of the JPEG image compression. In JPEG Image Compression, a quantizer follows the SVD. Such structural channel is beneficial for reducing difficulty in the whole JPEG compression/encoding. To overcome the problem of lossy compression implemented algorithm is designed in order to enhance the performance of compression algorithm with respect to performance evaluation parameters such as, Compression ratio , Bits per pixel , Peak signal to noise ratio, Mean squared error and Signal to noise ratio.