NDLI: Co-histogram and its application in remote sensing image compression evaluation

Content Provider	IEEE Xplore Digital Library
Author	Pengwei Hao Qingyun Shi Ying Chen
Copyright Year	2003
Description	Author affiliation: Center for Inf. Sci., Peking Univ., Beijing, China (Pengwei Hao; Qingyun Shi; Ying Chen)
Abstract	Peak signal-to-noise ratio (PSNR) has found its application as an evaluation metric for image coding, but in many instances it provides an inaccurate representation of the image quality. The new tool proposed in this paper is called co-histogram, which is a statistic graph generated by counting the corresponding pixel pairs of two images. For image coding evaluation, the two images are the original image and a compressed and recovered image. The graph is a two-dimensional joint probability distribution of the two images. A co-histogram shows how the pixels are distributed among combinations of two image pixel values. By means of co-histogram, we can have a visual interpretation of PSNR, and the symmetry of a co-histogram is also significant for objective evaluation of remote sensing image compression. Our experiments with two SAR images and a TM image using DCT-based JPEG and wavelet-based SPIHT coding methods perform the importance of the co-histogram symmetry.
Sponsorship	IEEE Signal Process. Soc
File Size	280793
File Format	PDF
ISBN	0780377508
ISSN	15224880
DOI	10.1109/ICIP.2003.1247210
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-14
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Image coding PSNR Pixel Image quality Application software Statistical distributions Probability distribution Transform coding Mean square error methods
Content Type	Text
Resource Type	Article

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