Analysis of Stereoscopic Image Compression Using Arithmetic Coding and Huffman Coding
Thafseela Koya Poolakkachalil, Saravanan Chandran · 2018 International Conference on Inventive Research in Computing Applications (ICIRCA) · 2018
Arithmetic coding and Huffman coding have been the recent trends for image compression due to their higher compression factor. This research article compares the results of the two methods namely stereoscopic compression using Arithmetic coding (SCAC) and stereoscopic compression using Huffman coding (SCHC). The storage requirement for stereoscopic images is twice or more when compared to the normal images, hence the motivation for the study of application of compression techniques for them. In this paper, the analysis is based on the application of these algorithms separately for each of the stereopair images. The recommended scheme is also compared with Binocular vision based objective quality assessment method for stereoscopic images (BVOQAM). From the experimental results, it is it is observed that SCAC is a better choice when compared to SCHC. It is also observed that Lossy SCAC has higher Compression Ratio when compared to Lossless SCAC while Lossless SCAC has higher Peak Signal to Nose Ratio when compared to Lossy SCAC. Hence Lossy SCAC is a better choice when high compression factor is required and Lossless SCAC is a better choice when the application requires high quality with no loss of information. From the experimental analysis, it is also observed that the proposed new SCAC scheme outperforms BVOQAM.