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Image Compression Based on Improved FFT Algorithm

Author(s): Juanli Hu | Jiabin Deng | Juebo Wu

Journal: Journal of Networks
ISSN 1796-2056

Volume: 6;
Issue: 7;
Start page: 1041;
Date: 2011;
Original page

Keywords: Image Compression | Fourier Transform | Quantization Table List | Compression Ratio | Coding and Decoding

Image compression is a crucial step in image processing area. Image Fourier transforms is the classical algorithm which can convert image from spatial domain to frequency domain. Because of its good concentrative property with transform energy, Fourier transform has been widely applied in image coding, image segmentation, image reconstruction. This paper adopts Radix-4 Fast Fourier transform (Radix-4 FFT) to realize the limit distortion for image coding, and to discuss the feasibility and the advantage of Fourier transform for image compression. It aims to deal with the existing complex and time-consuming of Fourier transform, according to the symmetric conjugate of the image by Fourier transform to reduce data storage and computing complexity. Using Radix-4 FFT can also reduce algorithm time-consuming, it designs three different compression requirements of non-uniform quantification tables for different demands of image quality and compression ratio. Take the standard image Lena as experimental data using the presented method, the results show that the implementation by Radix-4 FFT is simple, the effect is ideal and lower time-consuming.
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