【作者】 杨晓；

【导师】 齐国清； 王新年；

【作者基本信息】 大连海事大学 ， 信号与信息处理， 2008， 硕士

【摘要】 图像压缩是数字图像传输和存储以及多媒体技术中的关键问题,自适应压缩算法是提高压缩率的一种有效方法。本文研究基于内容特征的图像自适应压缩方法,旨在根据图像不同区域的内容特征,采用不同的压缩方法,使图像在恢复效果和压缩率上都有一定的改善和提高。主要研究内容包括自适应分块,自适应位分配以及自适应分块后的块效应处理。提出基于SUSAN算子的自适应分块方法。在自适应分块时,图像的内容特征用图像分块区域内的边缘信息量来表示,根据边缘信息量的多少将图像区域划分为平滑块和非平滑块两种类型。自适应分块的目的是对平滑块采用大尺寸分块压缩,对非平滑块采用小尺寸分块压缩,本论文最大分块尺寸为64~*64大小,最小分块尺寸为8~*8大小。自适应分块采用四叉树结构,四叉树分块的原则是基于SUSAN算子的边缘信息量提取。实验证明图像内容特征越平滑,基于SUSAN算子的自适应分块方法对图像压缩率提高的贡献就越大。提出基于DCT变换域重要系数的自适应位分配方法。重要系数是指幅值大的DCT变换系数。对于平滑块采用对量化表修正的方法实现重要系数的自适应位分配,对非平滑块采用量化表排序方法实现对重要系数的自适应位分配,对自适应量化时产生的地址信息采用地址聚类的编码方法。实验证明对非平滑块采用地址聚类编码方法减少DCT变换域重要系数的地址信息量,整个图像压缩率相对于标准JPEG提高大约20%-25%。基于SUSAN算子的自适应分块后图像会产生明显的块效应,采用基于人类视觉系统的块效应去除算法进一步提高图像的恢复质量。实验证明采用本论文的自适应压缩方法与标准JPEG压缩方法相比,在PSNR(峰值信噪比)的改善和压缩率的提高方面都有很好的表现。更多还原

【Abstract】 Image compression is the key problem in digital image transmission and storage , Adaptive compression is a useful method to imcrease the compression ratio. The discussion of this thesis is mainly the adaptive compression based on the content characters of images whose purpose is to improve the compression performance and the decoded images performance. The algorithm is mainly composed of adaptive partition , adaptive quantization and deblocking algorithm.The adaptive partition based on the SUSAN operator is divided into smooth block and non-smooth block according to the edge information. The edge information is used to measure the content characters. The biggest size of block is 64*64,and the smallest one is 8*8.The adaptive block adopts to quadtree segment .The method of edge detection is used to partition adaptively. Experiments have proved that the bigger the size of the smooth block is, the better the performance of the compression is.Adaptive quantization is based on the important coefficients which is defined as the content characters of images for non-smooth block. Adaptive quantization for smooth block modifies the quantization step to reserve the important coefficients . Adaptive quantization for non-smooth block resort the standard quantization step to reserve the important coefficients. But these important coefficients are needed to be presented by address information. In this thesis we make the address information aggregate to be helpful to compress. By aggregating the address, the address information is cut down and the compression performance advances 20%-25% compared to standard JPEG algorithm.As the result of adaptive partition, it exhibit noticeable blocking artifact near the block boundaries. The deblocking algorithm based on HVS is used to recover the missing image blocks. Experiments have proved the algorithm of this thesis is super to the standard JPEG algorithm in the improvement of PSNR and compress performance.更多还原