Using Kalman Filter Is Digital Signal Processing Based Filter

853 WordsJul 9, 20164 Pages
2.4 VIDEO DENOISING Nowadays digital cameras which is used to capture images and videos are storing it directly in digital form. But this digital data ie. images or videos are corrupted by various types of noises. It may cause due to some disturbances or may be impulse noise. To suppress noise and improve the image performances we use image processing schemes. In this paper they uses Kalman filter to remove the impulse noise. The Kalman filter is digital signal processing based filter. It estimates three states past, present and future of a system.[10] To remove noise from video sequences they utilize both temporal and spatial information. In the temporal domain, by collecting neighbouring frames based on similarities of all images, to remove noise from a video tracking sequence they given a low-rank matrix recovery phenomena. [11] 3. METHODOLOGY ADOPTED 3.1 Wavelength De-noising 3.2 Bilateral De-noising 3.1 WAVELENGTH DENOISING Basically a wavelet is small wave, which has its energy concentrated in time to give a tool for the analysis time varying phenomena. It is easier to remove noise from a contaminated 1D or 2D data using these algorithms to eliminate the small coefficient associated to the noise. In many signals, mostly concentration of energy is in a small number of dimensions and the coefficients of these dimensions are relatively large compared to other dimensions (noise) that has its energy spread over a large number of coefficients. In wavelet thresholding
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