Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

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

scholarly journals IMAGE ENHACEMENT PADA CITRA GESTUR TANGAN MENGGUNAKAN CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION

JOUTICA ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 454
Author(s):  
Natanael Putra Yustiantara
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Closed Circuit ◽  
Signal To Noise ◽  
Closed Circuit Television ◽  
Adaptive Histogram Equalization ◽  
Squared Error ◽  
Noise Ratio

Image Enhacement merupakan proses perbaikan kualitas citra yang dilakukan dengan menggunakan beberapa metode. Citra yang paling sering dilakukan perbaikan kualitas adalah citra digital. Citra digital sering digunakan pada pengolahan citra biometrik, pengenalan wajah, pengenalan tanda tangan, bahkan permasalahan pada Closed Circuit Television (CCTV). Penelitian ini bertujuan untuk memberikan perbedaan hasil proses image enhacement pada gambar yang telah tertangkap oleh CCTV. Penelitian ini menggunakan 3 buah metode yaitu, Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), dan Contrast Limited Adaptive Histogram Equalization (CLAHE) untuk melakukan perbaikan citra, sedangkan objek yang akan digunakan pada penelitian ini adalah citra gesture tangan. Dari hasil penelitian ini dapat dilihat bahwa Nilai MSE (Mean Squared Error) yang mendekati angka 0 adalah gambar yang menggunakan metode CLAHE (Contrast Limited Adaptive Histogram Equalization) dengan nilai sebesar 653.5. Untuk nilai PSNR (Peak Signal to Noise Ratio) sendiri nilai yang paling besar yaitu 29.9783476895 dengan menggunakan metode CLAHE.

Retinal Digital Image Quality Improvement as A Diabetes Retinopatic Disease Detection Effort

2020 ◽  
Vol 4 (2) ◽  
pp. 53-60
Author(s):  
Latifah Listyalina ◽  
Yudianingsih Yudianingsih ◽  
Dhimas Arief Dharmawan
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Image Quality ◽  
Digital Image ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Vital Role ◽  
Retinal Images ◽  
Signal To Noise ◽  
Noise Ratio

Image processing is a technical term useful for modifying images in various ways. In medicine, image processing has a vital role. One example of images in the medical world, namely retinal images, can be obtained from a fundus camera. The retina image is useful in the detection of diabetic retinopathy. In general, direct observation of diabetic retinopathy is conducted by a doctor on the retinal image. The weakness of this method is the slow handling of the disease. For this reason, a computer system is required to help doctors detect diabetes retinopathy quickly and accurately. This system involves a series of digital image processing techniques that can process retinal images into good quality images. In this research, a method to improve the quality of retinal images was designed by comparing the methods for adjusting histogram equalization, contrast stretching, and increasing brightness. The performance of the three methods was evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Signal to Noise Ratio (SNR). Low MSE values and high PSNR and SNR values indicated that the image had good quality. The results of the study revealed that the image was the best to use, as evidenced by the lowest MSE values and the highest SNR and PSNR values compared to other techniques. It indicated that adaptive histogram equalization techniques could improve image quality while maintaining its information.

The Influence of Alteration of kVp and mAs towards the Image Quality of Acrylic Using CBCT

2019 ◽  
Vol 829 ◽  
pp. 252-257
Author(s):  
Azhari ◽  
Yohanes Hutasoit ◽  
Freddy Haryanto
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Signal To Noise ◽  
Bite Block ◽  
Significant Difference ◽  
Noise Ratio ◽  
Post Hoc ◽  
Radiograph Image

CBCT is a modernized technology in producing radiograph image on dentistry. The image quality excellence is very important for clinicians to interpret the image, so the result of diagnosis produced becoming more accurate, appropriate, thus minimizing the working time. This research was aimed to assess the image quality using the blank acrylic phantom polymethylmethacrylate (PMMA) (C­5H8O2)n in the density of 1.185 g/cm3 for evaluating the homogeneity and uniformity of the image produced. Acrylic phantom was supported with a tripod and laid down on the chin rest of the CBCT device, then the phantom was fixed, and the edge of the phantom was touched by the bite block. Furthermore, the exposure of the X-ray was executed toward the acrylic phantom with various kVp and mAs, from 80 until 90, with the range of 5 kV and the variation of mA was 3, 5, and 7 mA respectively. The time exposure was kept constant for 25 seconds. The samples were taken from CBCT acrylic images, then as much as 5 ROIs (Region of Interest) was chosen to be analyzed. The ROIs determination was analyzed by using the ImageJ® software for recognizing the influence of kVp and mAs towards the image uniformity, noise and SNR. The lowest kVp and mAs had the result of uniformity value, homogeneity and signal to noise ratio of 11.22; 40.35; and 5.96 respectively. Meanwhile, the highest kVp and mAs had uniformity value, homogeneity and signal to noise ratio of 16.96; 26.20; and 5.95 respectively. There were significant differences between the image uniformity and homogeneity on the lowest kVp and mAs compared to the highest kVp and mAs, as analyzed with the ANOVA statistics analysis continued with the t-student post-hoc test with α = 0.05. However, there was no significant difference in SNR as analyzed with the ANOVA statistic analysis. The usage of the higher kVp and mAs caused the improvement of the image homogeneity and uniformity compared to the lower kVp and mAs.

Quality of Computed Tomography Pulmonary Embolism and Aortic Phase Images Acquired with Power Injection via an Arm Port

2017 ◽  
Vol 22 (2) ◽  
pp. 88-92
Author(s):  
Ryan Verity ◽  
David Leswick ◽  
Brent Burbridge ◽  
Rhonda Bryce ◽  
Hyun Lim
Keyword(s):  
Computed Tomography ◽  
Pulmonary Embolism ◽  
Image Quality ◽  
Thin Section ◽  
Signal To Noise Ratio ◽  
Contrast Injection ◽  
Signal To Noise ◽  
Streak Artifact ◽  
Noise Ratio

Abstract Background: The safety of power-injectable implanted arm ports is well established, but there is insufficient data to conclude that image quality of computed tomography resulting from contrast introduced via the port is of equal quality to images derived from contrast introduced via traditional peripheral access. The objective of this study was to determine whether the image quality of computed tomography pulmonary embolism and computed tomography aorta studies would differ when injecting contrast via an implanted arm port vs a peripheral intravenous site. We hypothesized that injecting via an implanted arm port would produce better-quality images, the result of more appropriate timing and less streak artifact. Methods: Scans from a provincial database search for patients who underwent a computed tomography pulmonary embolism or aorta study with contrast injection via the implanted arm port and thin section images available, were reviewed (pulmonary embolism studies n = 3, aorta studies n = 3). Only a limited number of patients were available for review because there are currently few patients with these ports in place and we limited evaluation to thin section images. Comparison was made with 6 control patients who did not have a port and had received a peripheral arm intravenous contrast injection for these study types. Objective measurements included signal-to-noise ratio and contrast-to-noise ratio of the pulmonary arteries (4 sites) and aorta (2 sites) as appropriate for scan type. Subjective analysis of image quality was performed by 2 radiologists. Results: Although sample size was limited, the implanted arm port group had similar or higher mean signal-to-noise ratio and contrast-to-noise ratio values at all sites. Subjective assessments showed the implanted arm port group to have similar or better opacification and diagnostic confidence; similar or less streak artifact was also observed at each of the sites. Conclusions: These exploratory results suggest that studies with implanted arm port injection can generate high-quality images on both objective and subjective assessment, similar to, or possibly better than, images generated from usual peripheral intravenous access for contrast injection.

An MMSE Overlay Cognitive Wireless System

2013 ◽  
Vol 5 (1) ◽  
pp. 1-13
Author(s):  
Monirosharieh Vameghestahbanati ◽  
Hasan S. Mir ◽  
Mohamed El-Tarhuni
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Wireless System ◽  
Transmitter Power ◽  
Channel Estimate ◽  
Squared Error ◽  
The Mean ◽  
Noise Ratio ◽  
New System

In this paper, the authors propose a framework that allows an overlay (new) system to operate simultaneously with a legacy (existing) system. By jointly optimizing the transmitter and the receiver filters of the overlay system, the sum of the mean-squared error (MSE) of the new system plus the excess MSE in the existing system due to the introduction of the overlay system is minimized. The effects of varying key parameters such as the overlay transmitter power and the amount of overlap between the legacy and the overlay systems are investigated. Furthermore, the sensitivity of the system to accuracy of signal-to-noise ratio (SNR) estimate and the channel estimate is also examined.

Determining the Quality of Compression in High Resolution Satellite Images Using Different Compression Methods

2015 ◽  
Vol 20 ◽  
pp. 202-217
Author(s):  
S. Sanjith ◽  
R. Ganesan
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Satellite Images ◽  
Signal To Noise Ratio ◽  
Joint Photographic Expert Group ◽  
Expert Group ◽  
Signal To Noise ◽  
High Resolution Satellite Images ◽  
Noise Ratio

Measuring the quality of image is very complex and hard process since the opinion of the humans are affected by physical and psychological parameters. So many techniques are invented and proposed for image quality analysis but none of the methods suits best for it. Assessment of image quality plays an important role in image processing. In this paper we present the experimental results by comparing the quality of different satellite images (ALOS, RapidEye, SPOT4, SPOT5, SPOT6, SPOTMap) after compression using four different compression methods namely Joint Photographic Expert Group (JPEG), Embedded Zero tree Wavelet (EZW), Set Partitioning in Hierarchical Tree (SPIHT), Joint Photographic Expert Group – 2000 (JPEG 2000). The Mean Square Error (MSE), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR) values are calculated to determine the quality of the high resolution satellite images after compression.

scholarly journals Skema Penyembunyian Data pada Gambar Berbasis Interpolasi Kubik B-Spline Menggunakan Metode Least Significant Bit (LSB)

2019 ◽  
Vol 5 (3) ◽  
pp. 255
Author(s):  
Garno Garno ◽  
Riza Ibnu Adam
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Image Interpolation ◽  
Cover Image ◽  
Original Image ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
B Spline ◽  
Squared Error ◽  
Noise Ratio

Maraknya kasus pencurian data menyebabkan sistem keamanan pesan harus ditingkatkan. Salah satu cara untuk mengamankan pesan adalah dengan memasukkan pesan ke dalam gambar digital. Penelitian ini bertujuan untuk meningkatkan kualitas gambar digital dalam sistem keamanan pesan tersembunyi. Teknik yang digunakan untuk keamanan pesan adalah steganografi. Cover image akan dikonversi menjadi bit piksel dalam domain spasial. Cover image digunakan dalam bentuk gambar digital dengan format .jpg. Teknik meningkatkan kualitas dan kapasitas gambar digital dilakukan dengan menambahkan dan meningkatkan bit piksel menggunakan metode interpolasi Cubik B-Spline. Cover image yang telah di interpolasi, kemudian disisipi pesan menggunakan metode least significant bit (LSB) untuk memperoleh stegoimage. Pesan yang diselipkan berbentuk file .doc, .docx, .pdf, .xls, .rar, .iso dan .zip dengan ukuran berbeda-beda kapasitasnya. Teknik uji dibuat dengan bantuan perangkat lunak MATLAB versi 2017a. Penelitian melakukan uji dengan mengukur nilai kualitas penyamaran dari stegoimage menggunakan Peak Signal to Noise Ratio (PSNR) dengan rata-rata perolehan stegoimage terhadap Original image 29.06 dB dan stegoimage terhadap Image interpolation 64.34 dB dan uji mean squared error (MSE) dengan rata-rata perolehan 97.54 dB pada Image interpolation terhadap original image dan 97.55 dB pada stegoimage terhadap original image, 0.13 dB nilai MSE stegoimage terhadap Image interpolation. Hasil uji pada penelitian dengan proses interpolasi pada coverimage dengan Cubic B-Spline mempengaruhi terhadap nilai samar atau Nilai PSNR.

scholarly journals Perbandingan Metode Contrast Enhancement pada Citra CT-Scan Kanker Paru-paru

Gravitasi ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 24-28
Author(s):  
Nurhidayah ◽  
Bannu Abdul Samad ◽  
Bualkar Abdullah
Keyword(s):  
Ct Scan ◽  
Contrast Enhancement ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Histogram Equalization ◽  
Mean Square ◽  
Signal To Noise ◽  
Adaptive Histogram Equalization ◽  
Noise Ratio

Abstrak: Di Indonesia kanker paru menjadi penyebab kematian kedua setelah kanker payudara. Angka mortalitas yang cukup tinggi, maka penentuan diagnosis lebih awal memegang peranan yang sangat penting dalam manajemen terapi. Kelemahan CT-Scan dalam mendiagnosa kanker paru-paru disebabkan oleh kontras citra yang rendah dan derau pada citra. Pada penelitian ini akan membandingkan metode contrast enhancement berbasis histogram equalization dan contrast limited adaptive histogram equalization untuk meningkatkan kualitas citra dengan menggunakan software Matlab. Namun, sebelumnya dilakukan reduksi noise dengan menggunakan metode median filter. Kinerja dari setiap metode dihitung dengan mencari nilai MSE (Mean Square Error) dan PSNR (Peak Signal to Noise Ratio) citra. Dari nilai MSE dan PSNR yang di dapatkan diperoleh nilai MSE dan PSNR terbaik pada metode contrast limited adaptive histogram equalization dengan nilai 653,434 dB dan 245,547 dB.

A Control Algorithm of LCD Dynamic Backlight Based on PSNR

2012 ◽  
Vol 241-244 ◽  
pp. 3014-3019 ◽  
Author(s):  
Xiao Bing Zhang ◽  
Xin Liu ◽  
Bo Liu ◽  
Jiang Hong Han ◽  
Hua Xia Wu
Keyword(s):  
Liquid Crystal ◽  
Image Quality ◽  
Power Consumption ◽  
Control Algorithm ◽  
Signal To Noise Ratio ◽  
Liquid Crystal Display ◽  
Gray Level ◽  
Quality Requirement ◽  
Signal To Noise

A new algorithm is proposed to adjust backlight luminance for local dimming of liquid crystal display (LCD) devices. PSNR (the peak signal-to-noise ratio) =30 is acted as the lowest standard to guarantee the quality of image in the algorithm. Based on the formula of PSNR=30, the square error value of the image distortion is gained. Then, luminance of backlight is gained dynamically by that the maximum gray level minus 1 into the formula proposed in the paper and decreases by one after each trial if the image quality requirement is not satisfied. In order to simplify the calculation, three important gray level values are selected to meet the requirements. The results show that the algorithm can greatly reduce the power consumption with guaranteeing the image quality and furthermore save much time in calculation and be better applied in hardware.

Sign in / Sign up

Export Citation Format

Share Document