Edge enhancement

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

Electronic rescreen technique for halftone pictures

Abstract: A method for rescreening a halftone image to produce an edge-enhanced halftone copy from a halftone original. The halftone original is scanned by a raster input scanner and the resultant analog voltage is compared to a reference voltage to produce a one bit per pixel bit stream, where a pixel is defined as the smallest image (picture) element discernable by the system. For example, in a raster input scanner using a CCD array, the smallest picture element, pixel, is the analog voltage output of one CCD cell. This voltage subsequently can be converted to a digital gray scale representation requiring a plurality of bits per pixel, or either analog or digital representation can be compared to an analog or digital reference voltage to produce a one bit pixel. A six bit per pixel gray scale output is produced therefrom by adding an integrated value and an edge enhancement value for each input pixel received. The integrated value is calculated by summing the number of one bits in the seven by nine bit section surrounding each pixel. The edge enhancement value is calculated by determining the difference between the number of one bits in the right and left halves, and upper and lower halves, of the six by seven bit section surrounding each pixel. A set of equations is used to process these differences to produce an edge enhancement value which is added to the integrated value. From this six bit per pixel gray scale output the six bit output can be preserved, or a halftone copy can be produced by any well-known process. A simple and inexpensive circuit to perform the above functions at high data rates is also disclosed.

A new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative for potential field data

Abstract: Edge detection and enhancement techniques are commonly used in recognizing the edge of geologic bodies using potential field data. We present a new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative which has the functions of both edge detection and enhancement techniques. First, we calculate the total horizontal derivative (THDR) of the potential-field data and then compute the n-order vertical derivative (VDRn) of the THDR. For the n-order vertical derivative, the peak value of total horizontal derivative (PTHDR) is obtained using a threshold value greater than 0. This PTHDR can be used for edge detection. Second, the PTHDR value is divided by the total horizontal derivative and normalized by the maximum value. Finally, we used different kinds of numerical models to verify the effectiveness and reliability of the new edge recognition technology.

Adaptive, quadratic preprocessing of document images for binarization

Abstract: This paper presents an adaptive algorithm for preprocessing document images prior to binarization in character recognition problems. Our method is similar in its approach to the blind adaptive equalization of binary communication channels. The adaptive filter utilizes a quadratic system model to provide edge enhancement for input images that have been corrupted by noise and other types of distortions during the scanning process. Experimental results demonstrating significant improvement in the quality of the binarized images over both direct binarization and a previously available preprocessing technique are also included.

The WMMR filters: a class of robust edge enhancers

Abstract: The authors develop a class of filters called weighted majority of m values with minimum range (WMMR/sup m/) that have the same impulse rejection properties as the median. They demonstrate a subclass of these filters (WMMR) that may be optimized for edge enhancement in one dimension in that their output converges to the closest perfect edge. One of these filters is shown to restore a class of noisy edges to the closest perfect edge on one pass. Applications in one and two dimensions are discussed and a two-dimensional simulation is provided comparing the WMMR to other filters for smoothing and edge enhancement. >

Acousto-optic image processing

Abstract: Acousto-optic processing of images is based on the angular selectivity of acousto-optic interaction resulting in spatial filtration of the image spectrum. We present recent theoretical and experimental investigations carried out in this field. Much attention is given to the analysis of the acousto-optic cell transfer function form depending on the crystal cut, the geometry of acousto-optic interaction, and the ultrasound frequency. Computer simulation results of the two-dimensional acousto-optic spatial filtration of some elementary images are presented. A new method of phase object visualization is suggested and examined that makes it possible to separate amplitude and phase information contained in an optical image. The potentialities of the acousto-optic image processing are experimentally demonstrated by examples of edge enhancement and optical wavefront visualization effects.