International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 1, January 2012) 118 Underwater Image Segmentation using CLAHE Enhancement and Thresholding Rajesh kumar Rai 1 , Puran Gour 2 , Balvant Singh 3 1, 2, 3 Department of Electronics & Communication NRI Institute of Information Science & Technology Bhopal, INDIA 1 raj.rai1008@gmail.com, 2 purrangour@rediffmail.com, 3 balvant.er@gmail.com Abstract - The objects in the underwater images are not clearly visible due to low contrast and scattering of light and the large noise present in the environment. Hence it is difficult to segmentation in such environment without losing the details of the objects. In this paper a method of segmentation is presented for underwater images, in which the image quality is first enhanced using contrast limited adaptive histogram equalization method, and then histogram thresholding is used to segment the objects. Paper discusses the comparative analysis of various Histogram thresholding techniques. For comparing the performance, mean square error and SNR used as parameters. The method is tested on various type of underwater image environment. Keywords - Image enhancement, Contrast limited Adaptive Histogram Equalization, image segmentation, Global Thresholding, Multi level Thresholding I. INTRODUCTION No segmentation technique is universally applicable, which works equally well for all kinds of images. Therefore, various segmentation approaches [1, 12, 15, and 16] have been developed which perform differently for different applications as well for different types of images. It is difficult to segmentation in underwater environment without losing the details of the objects. Although the low light in camera develops fast in recent years, and imaging velocity and image resolution ratio are improved greatly. But underwater images still have low contrast; unbalance gray scales and fuzzy edge of objects under the influence of the imaging condition and some character of water media. In underwater environment image get blurred due to poor visibility conditions and effects like “absorption of light”, “reflection of light”, “bending of light, “denser medium (800 times denser than air)”, and “scattering of light” etc. hence it is required to enhance the quality of the underwater images before processing. There is lot of research done for the improvement of image quality as [4, 12, 13, and 14]. The researchers have reviewed several techniques related to images enhancement viz “contrast stretching” “histogram equalization” [6] “contrast limited adaptive histogram equalization (CLAHE)” [5]. Here we are going to compare three enhancement techniques on the basis of SNR and mean square error as parameter. After enhancing the image quality segmentation is performed to extract the desired objects. Segmentation is typically associated with pattern recognition problems. It is considered the first phase of a pattern recognition process and is sometimes also referred to as object isolation as shown in Fig. 1. In this paper histogram thresholding is used for segmenting the background and objects in underwater environment. Then performance of global, local and multilevel thresholding is compared for different underwater environments. It found that with the combination of CLAHE method segmentation performs well for most of the images. Fig.1 Basic of Segmentation The remaining of the paper is organized as follows: Next Section describe the various type of image enhancement method and algorithm, section II describe the contrast stretching histogram equalization techniques, section III describe CLAHE method and its flow chart. Section IV discusses the Segmentation methods and, In Section V the results are compared. Section VI gives conclusion and future work.