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Logeshwaran, J.
- SVPA - The Segmentation Based Visual Processing Algorithm (SVPA) For Illustration Enhancements In Digital Video Processing (DVP)
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, K.L.N. College of Engineering, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, K.L.N. College of Engineering, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 3 (2022), Pagination: 2669-2673Abstract
At the present time photographic visual processing is rapidly moving towards the next stage. In addition, a variety of visual processing technologies are evolving, such as splitting image dimensions, calibration, pixel beautification, and high-resolution images. The impact of this digital visual processing technology has now greatly enhanced the opportunities for digital video processing technology and the source of its evolution. The vast industry of converting color images from black and white enables it to present even historical videos of the earlier period in a contemporary manner. In this paper, the segmentation based visual processing algorithm is proposed. The algorithm is designed to enhance resolution and clarity to a certain extent with multi-visual enhanced pixels. It also enhances the contrast, brightness and sharpness enhancement as it is much improved over the previous methods. This algorithm works on each image frame and enhances the overall visual function.Keywords
Visual Processing, Visual Processing, Image Dimension, Calibration, Pixel, Segmentation, Resolution, Contrast, Brightness, Sharpness
References
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- The Management and Reduction of Digital Noise in Video Image Processing by Using Transmission based Noise Elimination Scheme
Abstract Views :73 |
PDF Views:1
Authors
Affiliations
1 Department of Information Technology, K.L.N. College of Engineering, IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 Department of Electronics and Communication Engineering, SNS College of Technology, IN
4 SPC Free Zone, AE
1 Department of Information Technology, K.L.N. College of Engineering, IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 Department of Electronics and Communication Engineering, SNS College of Technology, IN
4 SPC Free Zone, AE
Source
ICTACT Journal on Image and Video Processing, Vol 13, No 1 (2022), Pagination: 2797-2801Abstract
Digital noise is an image defect that is approximately close to the pixel size and differs in brightness or color from the original image. Noise reduction plays an important role in the transmission, processing and compression of video footage and images. There are a large number of methods for removing noise from images, and they can be used not only by special processing programs, but also in some photo and video cameras. Despite this, there is still no universal filtering algorithm, because when processing an image, there is always a need to choose between preserving small details with properties such as size and noise to eliminate unwanted effects. In this paper, a management and reduction of digital noise in video image processing was discussed in the basis of transmission based noise elimination. In addition, that the proposed scheme easily overcomes the various types of noise. It will identify the spoil the image with another type of noise. Hence the noise affected part will eliminated and reduce the effects of noise.Keywords
Digital Noise, Pixel Size, Brightness, Color, Original Image, Transmission, Processing.References
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