Evaluation of SPIHT Compression Scheme for Satellite Imageries Based on Statistical Parameters
Nagamani .K1, A. G. Ananth2

1Nagamani.K, Visveswaraih Technical University, Belgaum, India.
2Dr..A.G. Ananth, Professor in TelecommunicationDepartment of R.V College of Engineering, Bangalore, India.

Manuscript received on April 15, 2012. | Revised Manuscript received on April 20, 2012. | Manuscript published on May 05, 2012. | PP: 127-130 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0537042212/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Non reversible and lossy image compression techniques is known to be computationally more complex as they grow more efficient, confirming the constraints of source coding theorems in information theory that a code for a (stationary) source approaches optimality the limit of infinite computation (source length). It has been observed that when a variety of images of different types are compressed using a fixed wavelet filter, the peak signal to noise ratios (PSNR) vary widely from image to image. This variation in PSNR can be attributed to the nature and inherent statistical characteristics of image. To explore the effect of various image features on the coding performance, a set of gray level image statistics have been analyzed by using SPIHT (Set Partitioning In Hierarchical Trees) algorithm. The Mean Square Error (MSE) and Peak Signal to Noise Ratios (PSNR) determined for an image depends on the statistical properties of the image and the compression scheme applied. The efficiency of the compression scheme can be evaluated by examining the statistical parameters of the image. In this paper various statistical parameters associated with the SPIHT compression scheme are derived for three different types of images namely standard Lena, satellite urban and rural imageries based on higher order statistics. The statistical parameters include higher order image statistics like Rate Distortion and Skewness and Kurtosis which describe the shape and symmetry of the image. The statistical parameters derived for a fixed rate and fixed level of decomposition for three types of images have been are used for the explanation of the Compression Ratio and Peak Signal to Noise Ratio (PSNR) achieved for the satellite imageries. The results show that urban images are better suited for SPIHT compression scheme compared to that of satellite rural image. The results of the analysis are presented in the paper.

Keywords: Compression ratio, EZW, MSE, SPIHT, PSNR