Showing papers on "Histogram equalization published in 1990"

A peak detection algorithm and its application to histogram-based image data reduction

Abstract: A new automatic peak detection algorithm is developed and applied to histogram-based image data reduction (quantization). The algorithm uses a peak detection signal derived either from the image histogram or the cumulative distribution function to locate the peaks in the image histogram. Specifically, the gray levels at which the peaks start, end, and attain their maxima are estimated. To implement data reduction, gray-level thresholds are set between the peaks, and the gray levels at which the peaks attain their maxima are chosen as the quantization levels. The results of using the proposed algorithm for data reduction purposes are presented in the case of various images.

Probability density histogram display

Abstract: Disclosed is a probability density histogram display for a digital oscilloscope which shows a probability density histogram display of an input signal waveform alongside the conventional voltage-versus-time time-domain display of the waveform The histogram shows the relative frequency of occurrence of voltage amplitude levels of the waveform The histogram is optional and shown simultaneously with the time-domain display of the waveform

Display of wide dynamic range infrared images from PtSi Schottky barrier cameras

Abstract: Twelve-bit digitized images taken with PtSi Schottky barrier detector arrays have been processed on Sun work stations. Two techniques for 8-bit global display are compared: the standard method of histogram equalization and a newly devised technique of histogram projection. The latter assigns equal dynamic range to each occupied level, while the former does so according to the density of the occupied levels. The projection technique generally gives distinctly superior results based on an extensive set of indoor, outdoor, day, and night imagery. For cases in which the two algorithms have complementary advantages, the techniques can be combined in effect by a weighting of their distribution functions, which often gives the desirable features of each. The new projection algorithm also can be used as a powerful and robust local contrast enhancement technique. An alternative method of contrast enhancement, a global algorithm based on modular (sawtooth) displays, affords a comparable degree of enhancement at less computational cost.

Ovulo-computer: application of image processing and recognition to mucus ferning patterns

Abstract: An approach to automatic prediction and detection of ovulation is described. It is based on the application of image processing techniques to the cervical mucus fern test, a popular clinical diagnostic method. The sequence of histogram equalization, filtering, edge detection, binarization, labeling, thinning, Hough transform, and automatic pattern recognition in a feature space is applied to microscopic images of the ferning patterns. This method permits decisions to be made based on quantitative data instead of the subjective evaluations that are presently used. >

A PC-based Vision System For Bone Measurement

Abstract: In recent years, computer vision techniques have been widely used in medical systems. This paper presents a new computer vision algorithm which is designed for measurement of skeletal growth. In practice, the overall system was fully developed on an IBM-PC. It has the advantages of eliminating the subjective variations resulted from the instability of human visual judgement and detecting children's abnormal skeletal growth in a short period of time. Two standard radiographs, taken from the same child at two time instants, were used in these analyses. This system consists of three stages: preprocessing, segmentation , and measurement. In the first stage, histogram equalization and autothresholding techniques were utilized to normalize the input radiograph and stretch the contrast. The segmentation determines the contour of each bone of interest. The measurement stage provides the necessary information for clinical diagnosis.

Digital filtering/enhancement/analysis of geologic long-range inclined asdic acoustic imagery

Abstract: Various digital filters, edge detectors, histogram modification, and three-dimensional display experiments are performed on mosaicked Geologic LOng-Range Inclined Asdic (GLORIA) acoustic imagery. These experiments have the motivation of establishing Navy capability for viewing the seafloor-especially in deep water and in three dimensions, detecting objects on the seafloor, and enhancing existing monochrome GLORIA imagery. It was found that a Gaussian filter with a kernel size of 5x 5 provided subjective enhancement to the lower intensity areas while some of the other filtering techniques, e.g., difference and gradient destroyed the dynamic range of the image. Kernel sizes were found to be extremely crucial in the experiments with this imagery, especially the median filter which did provide excellent smoothing of the imagery without sacrificing the edges. The digital mosaicking performed on this particular data set of acoustic imagery was determined to introduce multiple artificial artifacts. Image analysis showed the intensities (8 bit, 0-255)to follow the classic Gaussian distribution. Histogram equalization yielded exceptional results for adding contrast (which allows the determination ofgeologicalboundaries and detection of various seafloor objects. The vector intensity profile of the intensity offered an interesting future research objective, the correlation of acoustic imagery to bathymetry, the measurement of the depth of large bodies of water.