Digital Image Processing

R. Kathiravan ¹, R. Shanmugasundaram ¹, N. Santhiyakumari ¹

Affiliations
1 Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Anna University, Salem, Tamilnadu, IN

Abstract

Satellite images are being used in many fields of research. Resolution and contrast are the two important attributes of an image. This project deals with the enhancement of the quality of the image. Enhancement is used to make it easier for visual interpretation and understanding of imagery. The enhancement is done both with respect to the resolution and contrast. The advantage of digital imagery allows us to manipulate the digital pixel values in an image. Over the years, a variety of methods have been introduced to remove noise from digital images, such as Gaussian filtering, anisotropic filtering. This project deals with a new satellite image resolution enhancement technique based on the Contrast limited Adaptive Histogram Equalization (CLAHE) method, which proved that to be a simple and most effective technique for contrast enhancement of digital images. This project will yield better PSNR and MSE values. The experimental results show the superiority of the proposed method over conventional techniques.

Keywords

Satellite image, Resolution Enhancement, Mean Square Error, Peak Signal Noise Ratio, Histogram Equalization, Contrast Limited Adaptive Histogram Equalization.

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K. Papitha ¹, R. Shanmugasundaram ², N. Sandhiakumari ²

Affiliations
1 Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Kakapalayam , Salem, IN
2 Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Kakapalayam, Salem, IN

Abstract

Images are often corrupted by impulse noise in the procedures of image acquisition and transmission. In this paper, we propose an efficient denoising scheme and its algorithm for the removal of random –valued impulse noise. To achieve the goal of low cost, a low complexity algorithm is produced. We employ a decision tree based impulse noise detector to detect the noisy pixels, and an edge preserving filter to reconstruct the noisy pixels. An adaptive technology is used to enhance the effects of removal of impulse noise. Our experimental results demonstrate that the proposed technique can obtain better performance in terms of both quantitative evaluation and visual quality than the lower complexity methods. Moreover, the performance can be compared to the complexity methods. This design requires only low computational complexity and two line buffers. Its hardware cost is low cost and suitable to many real -time applications.

Keywords

Image Denoising, Impulse Noise, Impulse Detector.

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