In this paper, we investigate the denoising of image sequences i.e. video, corrupted with Gaussian noise and Impulse noise. In relation to single image denoising techniques, denoising of sequences aims to utilize the temporal dimension. This approach gives faster algorithms and better output quality. This paper focuses on the removal of different types of noise introduced in image sequences while transferring through network systems and video acquisition. The approach introduced consists of motion estimation, motion compensation, and filtering of image sequences. Most of the estimation approaches proposed deal mainly with monochrome video. The most usual way to apply them in color image sequences is to process each color channel separately. In this paper, we also propose a simple, accompanying method to extract the moving objects. Our experimental results on synthetic and natural images verify our arguments. The proposed algorithm’s performance is experimentally compared with a previous method, demonstrating comparable results.

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Machines like Internal Combustion Engines and gas turbines work on the principle of converting the heat energy into mechanical energy. Every effort is taken to elevate the operating temperature which in turn increases the output efficiency. However, the engine components cannot withstand such high temperatures and their life is seriously affected. The true gradient of the temperature to which these engine components are exposed is a wealth of knowledge for an engine designer. Conventional thermometry has got many limitations from measuring and mounting point of view and is unable to give the exact thermal gradient. Advancement in thermal mapping technique is required to enhance the development of these components. Comparatively thermal paints provide a better alternative to be used as temperature sensors. These paints change their color permanently when exposed to temperature. A proper calibration and automatic interpretation of these paints using digital image processing gives a reliable thermal contour. During the engine testing the carbon exhaust from the engine blackens the color of the thermal paint applied on the various components as it flows across it creating an obstacle in the color pattern (temperature) recognition. This article highlights the efforts taken in development and application of a filter which removes the effect of the carbon soot to denoise the degraded image and recover the original image to get the required temperature profile.

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