It includes parallel architectures , parallel software and parallel algorithm , etc . because the number of data in image processing is very huge , and the existence of convolution operation and matrix multiplication , it is possible that parallel algorithm design and implement can be used in image processing 并行處理技術(shù)領(lǐng)域非常廣泛,包括并行體系結(jié)構(gòu)、并行軟件和并行算法等。由于圖像處理過程中的數(shù)據(jù)量巨大,而且各種算法中大量卷積運算和矩陣乘法運算的存在,就為圖像處理過程中的并行算法設(shè)計和實現(xiàn)提供了可能。
Because the number of data in image disposal processing is very large , and the existence of many convolution operations and matrix multiplication operations in all kinds of algorithms , it is possible that parallel algorithm design and application can be used in image disposal processing 由于圖像處理過程中的數(shù)據(jù)量巨大,而且各種算法中大量卷積運算和矩陣乘法運算的存在,就為圖像處理過程中的并行算法設(shè)計和實現(xiàn)提供了可能。并行算法的設(shè)計是為了提高圖像處理的速度,在有限的空間和時間處理更多的圖像數(shù)據(jù)。
Set about from method of image data compression , the paper introduces wavelet and wavelet transform firstly . wavelet transform is an analytical method of time - scalable , which has the characteristics of multi - resolution , is partly transformed in space and frequency , and can realize self - adaptation in image analysis , but must carry on the huge convolution operation , it is complex 本文從圖像數(shù)據(jù)壓縮方法著手,介紹了小波和小波變換,小波變換是一種時間-尺度分析方法,它具有多分辨的特點,處理時進行的是空域和頻域的局部變換,可以用來實現(xiàn)對圖像的自適應(yīng)分析,但需進行龐大的卷積運算,計算復(fù)雜。