%0 Journal Article
%T The application of IAM in image decomposition<br>图像活跃度在图像分解中的应用
%A Cui Zhaohui
%A Liu Jiwei
%A Wang Zhiliang
%A Zhang Xiaoxing
%A <br>崔朝辉
%A 刘冀伟
%A 王志良
%A 张晓星
%J 中国图象图形学报
%D 2011
%I 
%X A concept of image compression based stratified variable blocksize decomposition is proposed after analyzing current image compression algorithms compreehensively. As the current most popular methods for static image compression, JPEG, JPEG2000 and fractal perform similarly when compressing different images with the same compression ratio: the more visually complex an image is, the lower a restored image quality is. After a large number of experiments, previous work shows that there is a clear relationship between all the three methods and image activity measure (IAM). According to the complexity of different image regions, stratified variable blocksize decomposition (SVBD) is achieved, using IAM and similarity as performance index. Particle swarm optimization (PSO) algorithm is used to find optimal approximation of the image blocks. Finally, by classifying the image blocks, some improvement to compression quality can be made.
%K image activity measure(IAM)
%K image decomposition
%K stratified
%K variable blocksize
%K PSO
%K image compression<br>图像活跃度量
%K 图像分解
%K 分层
%K 变块大小
%K 粒子群优化
%K 图像压缩
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=D6304BE3A5F615DAE84DDE9561D0593D&yid=9377ED8094509821&vid=7801E6FC5AE9020C&iid=94C357A881DFC066&sid=2868AE484E7BAD6B&eid=4D0B71A09FA5A2A5&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=19