Showing papers on "Histogram equalization published in 1987"

Regionally Adaptive Histogram Equalization of the Chest

Abstract: Advances in the area of digital chest radiography have resulted in the acquisition of high-quality images of the human chest. With these advances, there arises a genuine need for image processing algorithms specific to the chest, in order to fully exploit this digital technology. We have implemented the well-known technique of histogram equalization, noting the problems encountered when it is adapted to chest images. These problems have been successfully solved with our regionally adaptive histogram equalization method. With this technique histograms are calculated locally and then modified according to both the mean pixel value of that region as well as certain characteristics of the cumulative distribution function. This process, which has allowed certain regions of the chest radiograph to be enhanced differentially, may also have broader implications for other image processing tasks.

Endoscopic system for converting primary color images into hue, saturation and intensity images

Abstract: An endoscopic system provides a color picture by combining three primary color images with each other. The endoscopic system comprises an image converting device for performing a process of converting the respective primary color images into hue, saturation, and intensity images, and a process of reproducing three primary color images from the converted hue, saturation, and intensity images; and a histogram processing device for performing a process of obtaining a histogram based on at least one of the hue, saturation, and intensity images obtained by the image converting device, and executing at least one of a process of stretching the histogram and a process of shifting the histogram.

Binary quantification of an image having multiple levels of greys

Abstract: Method for transforming a video type image having multiple levels of greys into a binary image, method wherein each pixel is either white or black. With each pixel of the initial image there is associated a partial image centered on said pixel and comprising a plurality of pixels in at least one dimension. If the histogram of the grey levels of said partial image is considered as bimodal (D>E), a threshold (S) median with respect to said histogram is selected. If the histogram is considered as monomodal (D

A parameterized VLSI video-rate histogram processor

Abstract: A real-time video rate histogram processor has been designed, fabricated and tested. A pipelined architecture was chosen to support 10 MHz sample rates. The architecture was then implemented using high-level CAD tools to automate the design. Finally, the fabricated processor was connected to a second chip which implements a programmable look-up table function, to demonstrate real-time histogram equalization of 10 MHz video data.

A new iterative method with histogram equalization constraint for reconstructing image from phase

Abstract: In this paper, a new constraint named histogram constraint is introduced and its reasonability is analyzed also. As an example, we use the histogram equalization constraint in the iterative course of image reconstruction from phase. The experiment results showed that the histogram equalization constraint improved the convergent speed of the iterative method enormously.

Digital image processing of mandibular trabeculae on radiographs

Abstract: trabeculae by digital image processing. The 32 cases of normal subjects and the 13 cases of patients with mandibular diseases of ameloblastoma, primordial cysts, squamous cell carcinoma and odontoma were analyzed by their intra-oral radiographs in the right premolar regions. The radiograms were digitized by the use of a drum scanner densitometry method. The input radiographic images were processed by a histogram equalization method. The result are as follows : First, the histogram equalization method enhances the image contrast of the textures. Second, the output images of the textures for normal mandible-trabeculae radiograms are of network pattern in nature. Third, the output images for the patients are characterized by the non-network pattern and replaced by the patterns of the fabric texture, intertwined plants karakusa-pattern, scattered small masses and amorphous texture. Thus, these results ind i cates that the present digital image system is expected to be useful for revealing the texture patterns of the radiographs and in the future for the texture analysis of the clinical radiographs to obtain quantitative diagnostic findings.