Color image enhancement is very important in digital image processing. In image enhancement image features such as contrast, luminance can be improved at greater extent. In image enhancement the original information does not changes. There are various types of noise present in color images. To enhance the noisy images various image enhancement methods are used and these methods can gives better results than the original corrupted image. In this paper wavelet transform is used for color image enhancement. The proposed method enhances the contrast and luminance as well as removes the noise in the color image. In this proposed method daubechies wavelet transform and HIS color space used.

Different technologies are available on web. In the era of internet communication, systems should able to protect content such as pictures, videos against malicious modifications during their transmission. One of the important problems addressed in this is the authentication of the image received in a Communication. Tampering detection has significance in authentication of image. This paper presents support vector machine (SVM) based tampering detection system. In this a robust alignment (registration) method is proposed which makes use of an image hash component based on the Bag of Features (BOF) paradigm to localize the tampering. These BOF are clustered for effective image alignment. The support vector machine is optimal partitioning based linear classifier and at least theoretically better other classifier because only small numbers of classes required during classification SVM. The proposed signature is attached to the image before transmission and then analyzed at destination to recover the geometric transformations which have been applied to the received image. A block-wise tampering detection which uses histograms of oriented gradients (HOG) presentation is proposed. The proposed approach obtains better margin in providing an overall enhanced performance by reducing the training time while maintaining the accuracy.