Zobrazeno 1 - 6
of 6
pro vyhledávání: '"R. Vijaykumar"'
Publikováno v:
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. 35:1604-1616
Purpose One of the fundamental tasks in the field of image processing is image denoising. Images are often corrupted by different types of noise and the restoration of images degraded with random-valued impulse noise is still a challenging task. The
Publikováno v:
AEU - International Journal of Electronics and Communications. 68:1145-1155
This paper proposes a fast switching based median–mean filter for high density salt and pepper noise in images. The extreme minimum value and extreme maximum value of the noisy image are used to identify the noise pixels. In the filtering stage, th
Autor:
P. Jothibasu, V. R. Vijaykumar
Publikováno v:
ICIP
In this paper, a novel decision based adaptive median filter to remove blotches, scratches, streaks, stripes and random valued impulse noise in images is presented. The proposed method is a two stage algorithm. In the first stage the noise candidates
Publikováno v:
2008 International Conference on Signal Processing, Communications and Networking.
In this paper a new algorithm is proposed to remove Gaussian noise with edge preservation. The function of the proposed algorithm is to first find the pixel values along the boundary of the filtering window and then calculate its variance. If this va
Publikováno v:
International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).
In this paper a new efficient algorithm for the removal of Gaussian noise in gray scale and color images using adaptive window is presented. The function of the algorithm is to replace each corrupted pixel by a mean value of the pixels inside an adap
Autor:
V. R. Vijaykumar, G. Santhanamari
Publikováno v:
Journal of Electronic Imaging. 23:033011
A new switching-based trimmed median filter to remove high-density salt-and-pepper noise in digital images is proposed. Initially, a 3×3 sliding window is applied on each pixel in the noisy image. The minimum- and maximum-intensity values are trimme