Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.

Fractional vortex dipole phase filter

Abstract: In spatial filtering experiments, the use of vortex phase filters plays an important role in realizing isotropic edge enhancement. In this paper, we report the use of a vortex dipole phase filter in spatial filtering. A dipole made of fractional vortices is used, and its filtering characteristics are studied. It is observed that the filter performance can be tuned by varying the distance of separation between the vortices of the dipole to achieve better contrast and output noise suppression, and when this distance tends to infinity, the filter performs like a 1-D Hilbert mask. Experimental and simulation results are presented.

A new wavelet-based method for contrast/edge enhancement

Abstract: Contrast enhancement is usually achieved by histogram equalizing image pixel gray-levels in the spatial domain to redistribute them uniformly. Meanwhile, edge enhancement attempts to emphasize the fine details in the original image. But in the spatial domain it is hard to selectively enhance details at different scales. Moreover, in the spatial domain, applying contrast and edge enhancement techniques in different orders may yield different enhancement results. To overcome the above spatial domain enhancement issues, a new wavelet-based image enhancement method is proposed. The proposed method histogram-equalizes the approximation-coefficients. At the same time, it high-boost filters the detail-coefficients at selected resolution levels separately. The experiments show that utilizing the proposed method can achieve robust contrast and edge enhancement. Moreover, the computation cost in the wavelet domain is less than that in the spatial domain. This is especially true when considering that currently most images are already wavelet-compressed (the current JPEG 2000 standard is a wavelet based scheme).

Edge enhanced error diffusion with artifact correction in areas of highlights and shadows

Abstract: An error diffusion processor for preparing a document image for printing. Shadows and highlights regions stress error diffusion processes, because accumulated error cannot be easily compensated for in these regions. Edge enhancement emphasizes the problem by locally increasing error in order to maintain spatial detail of the image. The arrangement described puts an additional term into the error calculation that is a function of local intensity, with substantial value only in shadow and highlight regions to correct for edge enhancement artifacts.

Method of Image Edge Enhancement

Abstract: A method of image edge enhancement comprises: determining the edge trend for an image in accordance with the second order gradient value of a center pixel in different directions; performing interpolation operation with the center pixel; calculating absent color component of pixels; performing edge enhancement for the image in the interpolation module in accordance with original color component of the center pixel and the image edge trend based on the Bayer data. The image edge enhancement process takes into account the influence of the green component values of different pixels surrounding the center pixel, and adopts a noise-resistant, self-adaptive edge enhancement algorithm, to suppress noise on the image edge. Thus, the resulting image has a clear image edge. In addition, the fact that the process performs image edge enhancement in the interpolation module based on the Bayer data can significantly reduce the consumption of memory space.