A Comprehensive Research on Improved Hybrid Technique (dct+dwt) for Image Compression Using N Level of Decomposition by Spatial Density

Image compression is very important for efficient transmission and storage of images .Images contain large amounts of information that requires much storage space, large transmission bandwidths and long transmission times. Therefore it is advantageous to compress the image by storing only the essential information needed to reconstruct the image. Image compression is a widely addressed researched area. Many compression standards are in place. But still here there is a scope for high compression with quality reconstruction. Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are the most commonly used transformation. DCT has high energy compaction property and requires less computational resources. On the other hand, DWT is multi resolution transformation. This research paper proposed a scheme for image compression using DCT and DWT named as hybrid compression technique. The purpose of this technique is to provide high compression rate by preserving the quality of reconstructed image. The algorithm performs the Discrete Cosine Transform (DCT) on the Discrete Wavelet Transform (DWT) coefficients. MATLAB was used to analyse the results of Image Compression and concluded that hybrid DWT-DCT algorithm performs much better than the standalone JPEG-based DCT, DWT algorithms in terms of peak signal to noise ratio (PSNR), as well as visual perception at higher compression ratio.