Adaptive down-sampling and lapped transform-based image compression method

Abstract

The invention provides an adaptive down-sampling and lapped transform-based image compression method, and mainly solves the problems of low performance and high complexity existing in the prior down-sampling based compression method. The method comprises the following steps of: 1, adaptively down-sampling the prior image; 2, firstly performing lapped transform on the image after adaptive down-sampling between DCT blocks which are not subjected to the down-sampling, and then performing the DCT transformation on the whole image; 3, interweaving factors after transformation into a wavelet tree structure to obtain a low frequency subband DC and a high frequency subband AC; 4, performing the shape-adaptive DCT transformation on the low frequency subband DC, and interweaving the factors again; 5, by an object-oriented SPECK coding method, coding the factors with the wavelet tree structure to obtain a compressed bit stream; and 6, decompressing the bit stream transmitted to a decoding end toobtain a final re-constructed image. The method can obtain the performance higher than that of the prior image compression method under the condition of low bit rate, is low in complexity, and can beused for the low-bit-rate image coding which has strict requirements on complexity and real-time.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image compression method, which can be used to realize image compression with low complexity and low power consumption at a low code rate. Background technique [0002] Image, as the information carrier with the richest information content, has become one of the essential elements in the information age. In recent years, with the wide application of technologies such as video conferencing, videophone, high-definition television, remote monitoring and remote sensing imaging, images have become the main carrier of information exchange in people's lives, and high-resolution images are also used by different industries. need. With the development of imaging technology, many devices have been able to provide high-resolution digital images to meet people's requirements. However, the increase in resolution makes images contain more information, which puts forwar...

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Problems solved by technology

Although this type of method has been able to improve the coding performance at a relatively low bit rate, it still has the following disadvantages: First, because this type of method downsamples the entire image, whether it is a smooth area or an edge area, and the edge area It is difficult to estimate the correlation between regions and neighborhoods. Therefore, it is difficult to use general interpolation methods to upsample clear high-resolution images, which affects the quality of decoded images; the second is that such methods use complex High-degree interpolation method, so it is not suitable for some devices that have strict requirements on real-time performance and complexity

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