Limited redundant discrete small wave converting method

Abstract

A limited redundancy discrete wavelet transform method is used in the field of image processing, image fusion and signal processing. The invention firstly designs the filter, which is used respectively in the first class and the subsequent dissociation class, and then takes different sub-sampling rules according to different channels during the process of wavelet dissociation to, and uses the filter corresponding to its positive transformation and super-sampling rules during the process of inverse transformation. The invention, which uses different filter design methods in different class of discrete wavelet transform, and sub-sampling, super-sampling strategies according to different channels, can make the wavelet coefficients to have good invariance and appropriate redundancy. The invention can be applied to image processing, image fusion, signal processing and transformation, which can be used in radar, voice, geographic information processing and other home and military systems.

Description

technical field [0001] The present invention relates to a method used in the technical field of image processing, specifically, a limited redundancy discrete wavelet transform (LRDWT) method. Background technique [0002] Although the Fourier transform has been the cornerstone of transforming image and signal processing since the late 1950s, a new transform, called the wavelet transform, has recently made it easier to compress, transmit, and analyze many images and signals. Unlike the Fourier transform, whose underlying function is a sinusoidal function, the wavelet transform is based on small waves, called wavelets, with varying frequency and finite duration. This allows them to represent images or signals not only on the frequency scale, but also on the time scale. On the other hand, traditional Fourier transform can only provide time or frequency information, and local information is lost during the transform process. [0003] In 1987, in a new and effective signal proc...

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Problems solved by technology

In this paper, the discrete wavelet transform is firstly used for signal and image processing. This method is a non-redundant transform method. It has a big disadvantage: the obtained wavelet coefficients lack shift invariance, and the input signal is small and regular. The translation will cause the wavelet coefficients to change violently and irregularly in the respective bands and between levels

In this paper, a redundant wavelet transform method is proposed, which discards the down-sampling in the standard wavelet transform method to solve the above-mentioned shift invariance problem. However, it can generate highly redundant information in the decomposition coefficients, which will Greatly increase the amount of calculation

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