Assessment of Some Enhancement Methods of Renal X-ray Image

2020 ◽  
Vol 18 (12) ◽  
pp. 01-05
Author(s):  
Salim J. Attia

The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three quality image factors were done to assess the resulted images involved (Naturalness Image Quality Evaluator (NIQE), Perception based Image Quality Evaluator (PIQE) and Blind References Image Spatial Quality Evaluator (BRISQE)). The quality of images had been heightened by these methods to support the goals of diagnosis. The results of the chosen enhancement methods of collecting images reflected more qualified images than the original images. According to the results of the quality factors and the assessment of radiology experts, the CLAHE method was the best enhancement method.

2012 ◽  
Vol 468-471 ◽  
pp. 204-207
Author(s):  
Zhen Chong Wang ◽  
Yan Qin Zhao

For the low illumination and low contrast in the coal mine, images captured from the video monitor system sometimes are not so clear to help the related personal monitoring the production and safety of the mine. According to the special environment of coal mine, an image enhancement method was presented. In this method the impulse noise which is the mainly noise in the coal mine was first reduced with median filtering, then the low contrast and illumination was greatly improved with the improved adaptive histogram equalization. Experiments show that this method can improve the quality of images underground effectively.


Author(s):  
S. I. Rudikov ◽  
V. Yu. Tsviatkou ◽  
A. P. Shkadarevich

The problem of reducing the dynamic range and improving the quality of infrared (IR) images with a wide dynamic range for their display on a liquid crystal matrix with 8-bit pixels is considered. To solve this problem in optoelectronic devices in real time, block algorithms based on local equalization of the histogram are widely used, taking into account their relatively low computational complexity and the possibility of taking into account local features of the brightness distribution. The basic adaptive histogram equalization algorithm provides reasonably high image quality after conversion, but may result in excessive contrast for some types of images. In a modified algorithm of adaptive histogram equalization, the contrast is limited by a threshold by truncating local maxima at the edges of the histogram. This leads, however, to a deterioration in other indicators of image quality. This disadvantage is inherent in many algorithms of local histogram equalization, along with limited control over the characteristics of image reproduction quality. To improve the quality and expand the control interval for the characteristics of the reproduction of infrared images, the article proposes an algorithm for double reduction of the dynamic range of the image with intermediate control of the shape of its histogram. This algorithm performs: preliminary reduction of the dynamic range of the image based on adaptive equalization of the histogram, control of the shape of the histogram based on its linear or nonlinear compression, linear stretching of its central part and linear stretching (compression) of its lateral parts, final reduction of the dynamic range based on linear compression of the entire histograms. The characteristics of the proposed algorithm are compared with the characteristics of known algorithms for reducing the dynamic range and improving the image quality. The dependences of the characteristics of the quality of image reproduction after a decrease in their dynamic range on the control parameters of the proposed algorithm and recommendations for their choice taking into account the computational complexity are given.


2020 ◽  
Vol 12 (2) ◽  
pp. 80-88
Author(s):  
Claudia Kenyta ◽  
Daniel Martomanggolo Wonohadidjojo

When the photos are taken in low light condition, the quality of the results will not meet their expectation. Image Enhancement method can be used to enhance the quality of the photos taken in low light condition. One of the algorithms used is called Histogram Equalization (HE), that works using Histogram basis. The superiority of HE algorithm in enhancing the quality of the photos taken in low light condition is the simplicity of the algorithm itself and it does not need a high specification device for the algorithm to run. One variant of HE algorithm is Contrast Limited Adaptive Histogram Equalization (CLAHE). This paper shows the implementation of HE algorithm and its performance in enhancing the quality of photos taken in low light condition on Android based application and the comparison with CLAHE algorithm. The results show that, HE algorithm is better than CLAHE algorithm.


Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.


2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods


Author(s):  
S. Anand

Medical image enhancement improves the quality and facilitates diagnosis. This chapter investigates three methods of medical image enhancement by exploiting useful edge information. Since edges have higher perceptual importance, the edge information based enhancement process is always of interest. But determination of edge information is not an easy job. The edge information is obtained from various approaches such as differential hyperbolic function, Haar filters and morphological functions. The effectively determined edge information is used for enhancement process. The retinal image enhancement method given in this chapter improves the visual quality of the vessels in the optic region. X-ray image enhancement method presented here is to increase the visibility of the bones. These algorithms are used to enhance the computer tomography, chest x-ray, retinal, and mammogram images. These images are obtained from standard datasets and experimented. The performance of these enhancement methods are quantitatively evaluated.


1979 ◽  
Vol 18 (10) ◽  
pp. 1951-1957 ◽  
Author(s):  
Suguru Uchida ◽  
Yoshie Kodera ◽  
Hiroshi Inatsu
Keyword(s):  

1993 ◽  
Vol 306 ◽  
Author(s):  
F. Cerrina ◽  
G.M. Wells

AbstractIn proximity X-ray lithography there is no imaging system in the traditional sense of the word. There are no mirrors, lenses or other means of manipulating the radiation to form an image from that of a pattern (mask). Rather, in proximity X-ray lithography, mask and imaging systems are one and the same. The radiation that illuminates the mask carries the pattern information in the region of the wavefronts that have been attenuated. The detector (photoresist) is placed so close to the mask itself that the image is formed in the region where diffraction has not yet been able to deteriorate the pattern itself. The quality of the image formation then is controlled directly by the interaction between the mask and the radiation field. In turn, this means that both the illumination field and the mask are critical. The properties of the materials used in making the mask thus play a central role in determining the quality of the image. For instance, edge roughness and slope can strongly influence the image by providing the equivalent of a blur in the diffraction process. This blur is beneficial in reducing the high frequency components in the aerial image but it needs to be controlled and be repeatable. The plating (or other physical deposition) process may create variation in density (and thickness) in the deposited film, that will show up as linewidth variation in the image because of local changes in the contrast; the same applies to variations in the carrier membrane. In the case of subtractive process, variations in edge profile across the mask must be minimized.The variations in material composition, thickness and density may all affect the finale image quality; in the case of the resist, local variations in acid concentration may have strong effect in linewidth control (this effect is of course common to all lithographies).Another place where materials will affect the final image quality is in the condensing system. Mirrors will exhibit some degree of surface roughness, leading to a scattered radiation away from the central (coherent) beam. For scanning systems, this is not harmful since no power is lost in the scattering process and a blur is actually created that reduces the degree of spatial coherence. Filters may also exhibit the same roughness; typically it will not affect the image formation. The presence of surface (changes of reflectivity) or bulk (impurities) defects may however strongly alter the uniformity of the transmitted beam. This is particularly true of rolled Be filters and windows, which may include contaminants of high-Z materials. Hence, the grain structure of the window plays a very important role in determining image uniformity.Finally, a seemingly minor but important area is that of the gas used in the exposure area, typically helium. The gas fulfills several needs: heat exchange medium, to thermally clamp the mask to the wafer; low-loss X-ray transmission medium; protection from reactive oxygen radicals and ozone formation. Small amounts of impurities (air) may have a very strong effect on the transmission, and non-uniform distributions are particularly deleterious.All these factors need to be controlled so that the final image is within the required tolerances. Unfortunately, some of these are difficult to characterize in the visible (e.g., reflectivity variations) and testing at X-ray wavelengths is necessary. Although these obstacles are by no means unsurmountable, foresight is necessary in order to deliver a functional X-ray lithography process.This work was supported by various agencies, including ARPA/ONR/NRL and the National Science Foundation.


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