FPGA realization of DA-based 2D-Discrete Wavelet Transform for the proposed image compression approach

D. Shah, C. Vithlani
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引用次数: 2

Abstract

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.
FPGA实现基于数据的二维离散小波变换为提出的图像压缩方法
磁盘空间不足似乎是原始图像传输和存储过程中的一个主要挑战,这反过来又推动了对有效图像压缩技术的需求。尽管现在有很多可用的压缩技术,但任何更快、内存效率更高、更简单的新技术肯定更有可能满足用户的需求。在本文中,我们开发了基于小波的图像压缩算法,该算法采用了著名的分布式算法(DA)。在这里,为了提高压缩率,利用本文提出的RW块在每一级计算中进行小波系数的约简。在计算DWT系数后,我们应用DPCM(差分脉冲编码调制),这是一种提高图像可压缩性的变换技术。最后,将变换后的系数赋给霍夫曼编码器,该编码器通过合并最小概率符号来设计,从而使图像得到压缩。对于解压缩,在压缩图像中应用霍夫曼解码过程。然后对解码后的数据进行逆DPCM和逆DWT处理,得到解压缩后的图像。为了实现,在Active HDL工具中对基于数据分析的小波进行了仿真,并用verilog测试台对最终设计进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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