Belloulata Kamel, Konrad Janusz
Département de Génie Electrique et de Génie Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada.
IEEE Trans Image Process. 2002;11(4):351-62. doi: 10.1109/TIP.2002.999669.
Region-based functionality offered by the MPEG-4 video compression standard is also appealing for still images, for example to permit object-based queries of a still-image database. A popular method for still-image compression is fractal coding. However, traditional fractal image coding uses rectangular range and domain blocks. Although new schemes have been proposed that merge small blocks into irregular shapes, the merging process does not, in general, produce semantically-meaningful regions. We propose a new approach to fractal image coding that permits region-based functionalities; images are coded region by region according to a previously-computed segmentation map. We use rectangular range and domain blocks, but divide boundary blocks into segments belonging to different regions. Since this prevents the use of standard dissimilarity measure, we propose a new measure adapted to segment shape. We propose two approaches: one in the spatial and one in the transform domain. While providing additional functionality, the proposed methods perform similarly to other tested methods in terms of PSNR but often result in images that are subjectively better. Due to the limited domain-block codebook size, the new methods are faster than other fractal coding methods tested. The results are very encouraging and show the potential of this approach for various internet and still-image database applications.
MPEG - 4视频压缩标准所提供的基于区域的功能对于静止图像也很有吸引力,例如可用于对静止图像数据库进行基于对象的查询。一种流行的静止图像压缩方法是分形编码。然而,传统的分形图像编码使用矩形值域和定义域块。尽管已经提出了一些新方案,将小的块合并成不规则形状,但一般来说,合并过程不会产生语义上有意义的区域。我们提出了一种新的分形图像编码方法,该方法允许基于区域的功能;根据预先计算的分割图,逐区域对图像进行编码。我们使用矩形值域和定义域块,但将边界块划分为属于不同区域的段。由于这阻止了使用标准的差异度量,我们提出了一种适用于段形状的新度量。我们提出了两种方法:一种在空间域,一种在变换域。在提供额外功能的同时,所提出的方法在峰值信噪比(PSNR)方面与其他测试方法表现相似,但通常会产生主观上更好的图像。由于定义域块码本大小有限,新方法比其他测试的分形编码方法更快。结果非常令人鼓舞,显示了这种方法在各种互联网和静止图像数据库应用中的潜力。