| Abstrakt: |
The lack of disk space seems to be a major challenge during transmission and storage of raw images, which in turn pushes the demand for an efficient technique for compression of images. Although, lot of compression techniques are available today, any upcoming technique which is faster, memory efficient and simple surely has the greatest probability to hit the user requirements. In this paper, we have developed wavelet-based image compression algorithm using well-known Distributed Arithmetic (DA) technique. Here, to increase the compression rate, the reduction of wavelet coefficients is carried out in each level of computation with the help of RW block proposed in the paper. After computing the DWT coefficients, we apply DPCM (Differential pulse-code modulation) which is a transformation technique for increasing the compressibility of an image. Finally, the transformed coefficients are given to Huffman-encoder that is designed by merging the lowest probable symbols in such a way that, the images will get compressed. For decompression, the Huffman decoding procedure is applied in the compressed image. Furthermore, the inverse DPCM and inverse DWT is applied on the decoded data to obtain the decompressed image. For implementation, the DA-based wavelet is simulated in Active HDL tool and the final design is verified with verilog test benches. [ABSTRACT FROM PUBLISHER] |
