Image Processing refers Capturing and manipulating images to enhance or extract information. Image processing is a form of signal processing for which the input is an image, such as a photograph or frame. The output of image processing may be either an image or, a set of characteristics or parameters related to the image. This paper is about Night vision Technology, by definition, literally allows one to see in the dark, originally developed for military use. Night vision can work in two very different ways, depending on the technology used. Image enhancement-This works by using the lower portion of the infrared light spectrum. Thermal imaging -This technology operates by using the upper portion of the infrared light spectrum.

<p><span>Digital video watermarking is an effective way to protect the ownership of the multimedia contents. A novel compressed domain based digital video watermarking algorithm scheme is proposed by exploiting MPEG-2 structure. Watermark bits are embedded in DC and AC coefficients both of only smooth discrete cosine transform (DCT) blocks from selected I-frames in the original digital video. The algorithms never exploited entire frames but explore only three location from the subset of DCT blocks from the subgroup of I-frames only. This process maintains the perceptibility of the watermarked video. Two parameters, normalized correlation (NC) and bit error rate (BER) are used to evaluate the degree of similarity and dissimilarity respectively to check the robustness against image processing and video specific intentional and non-intentional attacks. The security of embedded watermark is enhanced by applying three cryptographic keys. The experimental results demonstrated that the better robustness and perceptibility achieved by comparing the results with the state of art. </span></p>

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The segmentation is the technique that is used to locate the objects of interest, partitioning the foreground from background. In other words segmentation is a procedure to group spatially adjacent image pixels into segments. Many research of the field is only for gray image. However, with the improvement of computer processing capabilities and the increased application of color images, the color image segmentation are more and more concerned by the researchers. In this paper, we are going to propose a model which can be used to differentiate min and max frequencies for both gray scale and color images, without losing any of the information from the images. After getting the result of both images, we will check which (color image or gray scale image) gives better response to the image segmentation techniques. So, here we will take the two methods threshold and edge detection.

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