Maximum error image compression method based on limited wavelet synopses

Abstract

The invention relates to a maximum error image compression method based on limited wavelet synopses. The maximum error image compression method is characterized by comprising the following steps of firstly, performing first-level line Haar wavelet decomposition on each line of a pixel matrix, storing the approximate value, filtering the generated detailed components, and reserving the required detailed components; performing first-level row Haar wavelet decomposition on each row, storing the approximate value, filtering the generated detailed components, and reserving the required detailed components; alternatively performing the line Haar wavelet decomposition and the row Haar wavelet decomposition on the newly generated approximate values, and filtering the detailed components until one approximate value is left; finally, using the approximate values and the detailed components to reconstruct data. The maximum error image compression method has the advantages that the error of each point of the reconstruction data is controlled within the setting range; compared with the existing maximum error image compression algorithm, the running time of the algorithm is shortened, and the reconstruction image quality is improved.

Description

technical field [0001] The invention relates to a maximum error image compression method based on a limited wavelet outline, which belongs to the technical field of image processing. Background technique [0002] With the development of information technology, image information is widely used in multimedia communication and computer systems. The remarkable feature of image data is the large amount of information. The huge amount of information obviously brings the problems of "not being able to store", "not being able to check quickly", and "not being able to calculate accurately" to the data processing. Although the channel transmission bandwidth is continuously widening, and the capacity of storage devices such as disks and hard disks is increasing, it still cannot solve the fundamental problem of huge data volumes. Data compression technology can save data storage space and improve the efficiency of data transmission. [0003] For images, generally used image compressio...

AI Technical Summary

Problems solved by technology

This method uses processed data to predict the current pixel value during prediction, which will lead to a decrease in prediction performance, resulting in a decrease in the quality of image reconstruction

Another example is to use the wavelet transform method to convert the error limit of the pixel threshold into the limit of the coefficient in the wavelet outline, and use the dynamic programming strategy to determine the selection of the coefficient threshold. However, the time complexity of this algorithm is relatively high, as O ( N 2 B log B ),in N represents the original data size, B Represents the size of the wavelet outline

If some scholars believe that the selection of coefficients in wavelet outlines in the past is selected from wavelet decomposition coefficients, this is not necessary and cannot guarantee the best quality wavelet outline, so they proposed a non-restricted wavelet outline technology, which The algorithmic complexity of the technique is polynomial complexity

Recently, some scholars have proposed a conversion compression algorithm (ie, Document 1: "On multidimensional wavelet synopses for maximum error bounds". Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2009: 646-661), which is also an unrestricted Wavelet outline technology, the time complexity of the algorithm is further reduced, as O ( N ), but the algorithm is not effective enough in the application of image compression, and its compression time and image reconstruction quality need to be further improved

[0005] The disadvantage of the existing maximum error image compression method algorithm is that the time complexity is high, and the reconstructed image quality has a large degree of distortion

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