Digital Image Processing

S. Deepa ¹, V. Sadasivam ²

Affiliations
1 Department of Information Technology, National College of Engineering, Tirunelveli, IN
2 PSN College of Engineering, Melathediyoor, Tirunelveli, IN

Abstract

Multispectral images are images with high spatial, spectral and radiometric resolution. Efficient multispectral image compression plays a key role in most of the geographical applications. The three important phases involved in a adaptive technique are transformation, clustering and encoding based on the resultant clusters. The existing methods like SPIHT, STW, WDR, and ASWDR are used as the base for Adaptive encoding techniques. The methods adopted are the recent wavelet compression techniques adopted for high dimensional images. The paper proposes the adaptive encoding technique and different combination of encoding techniques are evaluated and an efficient technique (E –Ad) is identified by comparing the results using the metrics Peak Signal to Noise Ratio as well as Compression Ratio. The proposed compression technique preserves the unique spectral characteristics of the multispectral image. The compressed image, can be efficiently used as preprocessing for many enhancement techniques and for object classification mechanisms. The E-Ad technique overtakes many of the state of art algorithms.

Keywords

ASWDR, E–Ad, SPIHT, STW, WDR.

Full Text

     

G. Madasamy Raja ¹, V. Sadasivam ²

Affiliations
1 Department of Computer Science and Engineering, M.E.T. Engineering College, Nagercoil, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, IN

Abstract

Digital image enhancement techniques are used for improving the quality of the digital image. Contrast enhancement, one of the digital image enhancement techniques, is a process that normalizes the gray level of the input image so that sudden and unexpected changes in the illumination are removed. Image contrast enhancement techniques are used for extracting several hidden image characteristics from the image background. This paper proposes a new methodology for image contrast enhancement that is based on the concept of normalization of the image contrast with the help of morphological filters. Two methods are proposed here for detecting the image background from the images which are captured with poor lighting, one method uses the combination of opening and closing morphological filters and another method uses top-hat by opening morphological filter. Also, the performance of proposed algorithm for image contrast enhancement is demonstrated against a recently proposed method.

Keywords

Image Background Detection, Image Contrast Enhancement, Morphological Filters, Weber Contrast Measure.

Full Text