Efficient image coding for access to pixel ranges (MA-P5)

Author(s) : Sehoon Yea (Rensselaer Polytechnic Institute, USA) Amir Said (Hewlett Packard Laboratories, USA) William Pearlman (Rensselaer Polytechnic Institute, USA)

Abstract : Many technical imaging applications such as coding ``images'' of digital elevation maps, require extracting regions of compressed images in which the pixel values are within a pre-defined range, and there is a need for coding methods that allow finding these regions efficiently, without having to decompress the whole image. In this paper, we first show that many of the linear transforms commonly used for image compression can be used for that purpose by proving that the inclusion of nonlinear factors (like minimum or maximum pixel value in a block) does not render the transformation irreversible, and can be made to have very limited impact on the compression efficiency. Next, we study the choices for coding the minimum and maximum values simultaneously, while providing quick access to pixel range and efficient compression.

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