Volume I, Issue VI, November 2014 IJRSI ISSN 2321 - 2705 www.rsisinternational.org/IJRSI.html Page 37 Comparative Study of Linear and Non-linear Contrast Enhancement Techniques Kalpit R. Chandpa #1 , Ashwini M. Jani #2 , Ghanshyam I. Prajapati #3 # Department of Computer Science and Information Technology Shri S’ad Vidya Mandal Institute of Technology Bharuch 392-001, Gujarat, India Abstract— Image enhancement is the process of improving the quality of image by using various techniques. There are so many techniques for image enhancement and every technique produces different result for different images. Contrast enhancement is one of the techniques of Image Enhancement that produces an image that subjectively looks better than the original image by changing the pixel intensities. In this paper, the various contrast enhancement techniques are compared with respect to image enhancement. We compared three cases: In the first case comparison between the linear contrast methods, in second case comparison between the non-linear contrast methods and third case comparison between linear and non-linear contrast methods. Analysis studies are explained and experiments show that Piecewise contrast method gives better result comparing with other techniques of linear contrast enhancement. For nonlinear contrast enhancement techniques, Histogram Equalization gives better result comparing with other non-linear contrast methods and non-linear contrast methods give better result than linear contrast methods. Keywords— Linear Contrast Enhancement, Non-Linear, Contrast Enhancement, Contrast Stretching, Histogram Equalization. I. INTRODUCTION he main objective of image enhancement is to process a given image so that the result is more suitable than the original image for a specific application. It accentuates or sharpens image features such as edges, boundaries, or contrast to make a graphic display more helpful for display and analysis. The enhancement doesn't increase the inherent information content of the data, but it increases the dynamic range of the chosen features so that they can be detected easily. Contrast stretching is a simple image enhancement technique that attempts to improve the contrast in an image by `stretching' the range of intensity values it contains to span a desired range of values. Histogram Equalization is performed by remapping the gray levels of the image based on the probability distribution of the input gray image levels. It flattens and stretches the dynamic range of the image’s histogram and resulting in overall contrast enhancement. II. IMAGE ENHANCEMENT The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide better input for other automated image processing techniques. Image enhancement transforms images to provide better representation of image. Image enhancements techniques are used to make images lighter or darker, or to increase or decrease contrast, or to remove undesired characteristics of an image such as colour cast. The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide `better' input for other automated image processing techniques. Image enhancement is generally used in the following three cases: noise reduction from image, contrast enhancement of the very dark, low contrast and bright image, and high light the edges of the objects in a blurring image. Noise reduction is the process of removing noise form a signal or an image. In general, images taken with both digital camera and conventional film cameras will pick up noise from a variety of sources. Therefore, it is required that the noise is removed for many further uses of these images. Contrast enhancement is acquiring clear image through brightness intensity value redistribution. That is, this is enhancing features as stretching interval between dark and brightness area. A. Image Enhancement Techniques The greatest difficulty in image enhancement is quantifying the criterion for enhancement and, therefore, a large number of image enhancement techniques are empirical and require interactive procedures to obtain satisfactory results. Image enhancement methods can be based on either spatial or frequency domain techniques [1]. Fig. 1: Image Enhancement techniques [9]. The main aim of enhancement is to process an image so that the result is more suitable than the original image for analysis purpose. Here we concerned two main Image Enhancement techniques Linear and Non-linear Contrast Enhancement and their result analysis. Fig.1 shows some important image enhancement techniques. III. CONTRAST ENHANCEMENT Low-contrast images can result from poor illumination, lack of dynamic range in the image sensor, or even wrong T