scholarly journals Image Enhancement Using Weighted Bi-Histogram Equalization

2021 ◽  
Vol 15 ◽  
pp. 98-101
Author(s):  
Thaweesak Trongtirakul ◽  
Nattapong Phanthuna
Keyword(s):  
Signal Processing ◽  
Probability Density Function ◽  
Image Enhancement ◽  
Human Perception ◽  
Digital Signal ◽  
Histogram Equalization ◽  
Area Ratio ◽  
Original Image ◽  
Weighted Factor

Image enhancement is one of using in various digital signal processing areas. Advances in microcontrollers, microcomputers and computers have developed traditional algorithms in order to improve the quality of the resulting image and have implied many avenues to the design of new innovations using various techniques. This paper proposes contrast enhancement using weighted bi-histogram equalization based on distributed area ratio. Moreover, this technique must use a weighted factor which is calculated by the ratio of the histogram distribution. Likewise, an original image will be equalized by the modification of the probability density function of the gray levels. As result of the experiment, the contrast of resulting image is improved for implement and human perception – as well as also reduces the absolute mean brightness error (AMBE) than the traditional technique of image enhancement.

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

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.

A Modified Multi Scale Retinex with Color Restoration Algorithm for Automatic Enhancement of Landsat-5 Remote Sensing Image

2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Color Constancy ◽  
Human Perception ◽  
Histogram Equalization ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Dynamic Range Compression ◽  
Restoration Algorithm ◽  
Color Restoration

The retinex is a human perception based image processing algorithm which provides color constancy and dynamic range compression. The multi scale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. But the MSRCR results suffer from lower global brightness and partial color distortion. In order to improve the MSRCR method, this paper presents a modified MSRCR algorithm to Landsat-5 image enhancement considering percent liner stretch and histogram adjustment. Finally, the effect of modified MSRCR method on Landsat-5 image enhancement is analyzed and the comparison with other color adjustment methods such as gamma correction and histogram equalization is reported in the experimental results.

scholarly journals Enhancement of Satellite Imagesusing Image Sharpening Technique

2019 ◽  
Vol 8 (6S2) ◽  
pp. 351-354
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Histogram Equalization ◽  
Grayscale Image ◽  
Original Image ◽  
High Quality ◽  
Wide Range ◽  
Equalization Technique ◽  
The Difference

In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.

scholarly journals Histogram Adjustment of Images for Improving Photogrammetric Reconstruction

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4654
Author(s):  
Piotr Łabędź ◽  
Krzysztof Skabek ◽  
Paweł Ozimek ◽  
Mateusz Nytko
Keyword(s):  
Image Enhancement ◽  
High Efficiency ◽  
Color Image ◽  
Histogram Equalization ◽  
Reconstruction Accuracy ◽  
Reconstruction Process ◽  
Reference Models ◽  
Color Models ◽  
Selection Of

The accuracy of photogrammetric reconstruction depends largely on the acquisition conditions and on the quality of input photographs. This paper proposes methods of improving raster images that increase photogrammetric reconstruction accuracy. These methods are based on modifying color image histograms. Special emphasis was placed on the selection of channels of the RGB and CIE L*a*b* color models for further improvement of the reconstruction process. A methodology was proposed for assessing the quality of reconstruction based on premade reference models using positional statistics. The analysis of the influence of image enhancement on reconstruction was carried out for various types of objects. The proposed methods can significantly improve the quality of reconstruction. The superiority of methods based on the luminance channel of the L*a*b* model was demonstrated. Our studies indicated high efficiency of the histogram equalization method (HE), although these results were not highly distinctive for all performed tests.

An Image Enhancement Method Based on the Coal Mine Monitoring System

2012 ◽  
Vol 468-471 ◽  
pp. 204-207
Author(s):  
Zhen Chong Wang ◽  
Yan Qin Zhao
Keyword(s):  
Image Enhancement ◽  
Coal Mine ◽  
Impulse Noise ◽  
Histogram Equalization ◽  
Video Monitor ◽  
Low Contrast ◽  
Adaptive Histogram Equalization ◽  
Enhancement Method ◽  
Special Environment

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.

Signal rectifying and detecting in the NI ELVIS complex

2021 ◽  
pp. 63-71
Author(s):  
E.B. Solovyeva ◽  
◽  
K.S. Ezerov ◽  
Yu.M. Inshakov ◽  
◽  
...  
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Electrical Engineering ◽  
Digital Signal ◽  
Nonlinear Circuit ◽  
Signal Conversion ◽  
Half Wave ◽  
Nonlinear Distortions ◽  
Visualization Tools

A half-wave diode rectifier is represented as a nonlinear circuit to study in a laboratory course of electrical engineering. The control and measurement complex NI ELVIS effectively displays the nonlinear circuit properties using oscillograms and spectrograms of signals. The coefficients of ripples and nonlinear distortions are calculated. They help to evaluate the influence of the circuit parameters on the quality of signal conversion when rectifying and detecting. The advantages of the NI ELVIS complex consist in, for instance, the real-time digital signal processing, the visualization of results, the ergonomic visualization tools. These advantages provide clarity and precision in the presentation of complex nonlinear processes in electrical engineering.

scholarly journals Effect of Multichannel Digital Signal Processing on Loudness Comfort, Sentence Recognition, and Sound Quality

2006 ◽  
Vol 17 (10) ◽  
pp. 681-707 ◽  
Author(s):  
Karen M. Mispagel ◽  
Michael Valente
Keyword(s):  
Signal Processing ◽  
Hearing Aids ◽  
Dynamic Range ◽  
Digital Signal ◽  
Sound Quality ◽  
Sentence Recognition ◽  
Hearing In Noise ◽  
Subjective Loudness ◽  
Noise Test

This study evaluated the effect of increasing the number of processing channels from 32- to 64-signal processing channels on subjects' loudness comfort and satisfaction, sentence recognition, and sound quality of his or her own voice. Ten experienced hearing aid users with mild-to-moderate sensorineural hearing loss wore behind-the-ear (BTE) hearing aids with Adaptive Dynamic Range Optimization (ADRO™) signal processing for a period of six weeks in the 32-channel and 64-channel conditions. Results revealed no significant differences in loudness comfort or satisfaction for the majority of sound samples as measured by the Subjective Loudness Test and Environmental Sounds Questionnaire. No significant differences in sentence recognition between the two processing conditions were found as measured by the Hearing In Noise Test (HINT). Additionally, no subjective differences in sound quality of subjects' own voice were determined by the Listening Tasks Questionnaire.

Modified Distributed Arithmetic Concept for Implementations Targeted at Heterogeneous FPGAs

2010 ◽  
Vol 56 (4) ◽  
pp. 345-350
Author(s):  
Mariusz Rawski
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Efficient Implementation ◽  
Heterogeneous Structure ◽  
Distributed Arithmetic ◽  
Architecture Exploration ◽  
Flexible Architecture ◽  
Heterogeneous Fpga

Modified Distributed Arithmetic Concept for Implementations Targeted at Heterogeneous FPGAsDistributed Arithmetic (DA) plays an important role in designing digital signal processing modules for FPGA architectures. It allows replacing multiply-and-accumulate (MAC) operations with combinational blocks. The quality of implementations based on DA strongly depends on efficiency of methods that map combinational DA block into FPGA resources. Since modern FPGAs have heterogeneous structure, there is a need for quality algorithms to target these structures and the need for flexible architecture exploration aiding in appropriate mapping. The paper presents a modification of DA concept that allows for very efficient implementation in heterogeneous FPGA architectures.

scholarly journals A Novel Technique for Automatic Image Enhancement using HTHET Approach

2019 ◽  
Vol 8 (1) ◽  
pp. 26-31
Author(s):  
V. Murali ◽  
T. Venkateswarlu
Keyword(s):  
Contrast Enhancement ◽  
Image Enhancement ◽  
Information Content ◽  
Optimization Method ◽  
Histogram Equalization ◽  
Original Image ◽  
Enhancement Technique ◽  
Novel Technique ◽  
Equalization Technique ◽  
Histogram Transformation

Image enhancement techniques are methods used for producing images with better quality than the original image. None of the existing methods increase the information content of the image, and are usually of little interest for subsequent automatic analysis of images. In this paper, automated Image Enhancement is achieved by carrying out Histogram techniques. Histogram equalization (HE) is a spatial domain image enhancement technique, which effectively enhances the contrast of an image. We make use of Transformation and Hyperbolization techniques for automatic image enhancement. However, while it takes care of contrast enhancement, a modified histogram equalization technique, Histogram Transformation and Hyperbolization Equalization Technique (HTHET) using optimization method is proposed using EQHIST and LINHIST.

scholarly journals Analysis of speech waveform quantization methods

2008 ◽  
Vol 18 (1) ◽  
pp. 19-22
Author(s):  
Predrag Tadic ◽  
Zeljko Djurovic ◽  
Branko Kovacevic
Keyword(s):  
Signal Processing ◽  
Probability Density Function ◽  
Digital Signal Processing ◽  
Speech Signal ◽  
Digital Signal ◽  
Quantization Noise ◽  
Signal Processing Algorithm ◽  
Memory Space ◽  
Pdf Estimation ◽  
Digital Signal Processing Algorithm

Digitalization, consisting of sampling and quantization, is the first step in any digital signal processing algorithm. In most cases, the quantization is uniform. However, having knowledge of certain stochastic attributes of the signal (namely, the probability density function, or pdf), quantization can be made more efficient, in the sense of achieving a greater signal to quantization noise ratio. This means that narrower channel bandwidths are required for transmitting a signal of the same quality. Alternatively, if signal storage is of interest, rather than transmission, considerable savings in memory space can be made. This paper presents several available methods for speech signal pdf estimation, and quantizer optimization in the sense of minimizing the quantization error power.

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