Abstract
Image compression is very significant for a lot of applications that involve an enormous amount data storage, transmission, and retrieval such as for endoscopic imaging. To save the wireless transmission power and bandwidth, image compression is very important. Several transformations are used for data compression. The two most commonly techniques used to achieve an efficient compression are the DCT and the DWT algorithms. When using the DWT lifting algorithm, a higher level of DWT lifting decomposition stages needs to be considered to achieve a higher compression. Moreover, this will increase computational complexity and degrade the image quality. Additionally, utilizing CORDIC-Loeffler-based DCT, a higher number of blocks image is needed to be processed, due to smaller size data block used. Hence, the idea is to explore the advantages of both algorithms DWT lifting and CORDIC-Loeffler-based DCT to achieve a higher compression ratio with an acceptable image quality. Also, we introduce a lossless context adaptive variable-length-coding (CAVLC) compression technique to encode the compressed bit streams at compression stage. The CAVLC produces coding with higher efficiency than the conventional VLC coding. Therefore, an efficient hybrid DWT lifting based on CORDIC-Loeffler-based DCT and the CAVLC algorithm is suggested in this paper. Simulation has been conducted on several endoscopic images. The experimental results demonstrate that our suggested hybrid algorithm achieves a higher compression ratio while preserving the visual image quality. Hence, based on experimentally obtained results, the proposed hybrid DWT lifting-CORDIC-Loeffler-based DCT and CAVLC algorithm performs much better than DWT lifting and CORDIC-Loeffler-based DCT algorithms in terms of PSNR.