Big Data Compression Using Anamorphic Stretch Transform

نویسندگان

  • Mohammad H. Asghari
  • Bahram Jalali
چکیده

The proliferation of image data is a major contributor to the big data and the problems associated with its storage and transmission. In this paper, we present applications of the recently introduced Anamorphic Transform to enhancing the performance of two popular image compression methods, JPEG and JPEG 2000. The transformation increases the spatial coherence resulting in superior compression without sacrificing the image quality. We present examples showing improved compression of various types of images contributing to big data including medical, security and surveillance, astronomy, and satellite images.

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تاریخ انتشار 2014