Multifocus Fusion Image Enhancement Based on Image Subtraction Angiography and NSML

2020 ◽  
Vol 57 (20) ◽  
pp. 201016
Author(s):  
田帅 Tian Shuai ◽  
任亚飞 Ren Yafei ◽  
邵馨叶 Shao Xinye ◽  
邵建龙 Shao Jianlong
Keyword(s):  
Image Enhancement ◽  
Fusion Image ◽  
Image Subtraction

scholarly journals Spatial domain image enhancement techniques for acute myeloid leukemia (M1,M4,M5,M7)

2019 ◽  
Vol 14 (1) ◽  
pp. 250
Author(s):  
A.S. A.Salam ◽  
M.N. M.Isa ◽  
M. I. Ahmad
Keyword(s):  
Acute Myeloid Leukemia ◽  
Image Enhancement ◽  
Myeloid Leukemia ◽  
Signal To Noise Ratio ◽  
Spatial Domain ◽  
Signal To Noise ◽  
Image Subtraction ◽  
Image Sharpening ◽  
Contrast Stretching ◽  
Acute Myeloid

<p class="Abstract"><span>In this paper, several techniques of image enhancement spatial domain is elucidated and analyzed for the purpose of enhancing Acute Myeloid Leukemia (AML) subtype of M1, M4, M5 and M7. The techniques involved contrast stretching of greyscale images, image subtraction and image sharpening. The three methods compared with one another to achieve the highest PSNR value for the suitability technique of AML subtypes (M1, M4, M5 and M7). Firstly, subtypes images converted into grayscale. Then, each four images tested with contrast stretching techniques followed by image subtraction and image sharpening. The performances were evaluated based on Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). Due to its higher value obtained, image sharpening is a good enhancement techniques for Acute Myeloid Leukemia with 68.2083 dB and the lowest MSE achieved of 0.0103.</span></p>

scholarly journals Grasping Control of a UVMS Based on Fusion Visual Image Enhancement

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wei Chen ◽  
Lei Wang ◽  
Yuhang Zhang ◽  
Xu Li ◽  
Weiran Wang
Keyword(s):  
Image Enhancement ◽  
Control Method ◽  
Visual Image ◽  
Fusion Image ◽  
Constrained Problems ◽  
Underwater Environment ◽  
Target Ranging ◽  
Retinex Theory ◽  
Resolution Algorithm ◽  
Enhancement Algorithm

The Underwater Vehicle Manipulator System (UVMS) is an essential equipment for underwater operations. However, it is difficult to control due to the constrained problems of weak illumination, multidisturbance, and large inertia in the underwater environment. After the UVMS mathematical model based on water flow disturbance is established, fusion image enhancement algorithm based on Retinex theory is proposed to achieve fine perception of the target. The control method based on redundant resolution algorithm is adopted to establish the anti-interference controller of the manipulator, which can compensate the internal and external uncertain interference. Finally, stable underwater operation is realized. The target ranging method is used to solve the angle of each joint of the manipulator to complete the tracking and grasping of the target. Underwater experiments show that the algorithm can improve the clarity of underwater images, ensure the accuracy of robot capture, and optimize the UVMS control performance.

Exploring Coronal Structures with SOHO

2000 ◽  
Vol 179 ◽  
pp. 403-406
Author(s):  
M. Karovska ◽  
B. Wood ◽  
J. Chen ◽  
J. Cook ◽  
R. Howard
Keyword(s):  
Solar Corona ◽  
Image Enhancement ◽  
Coronal Mass Ejections ◽  
Dynamical Evolution ◽  
Small Scale ◽  
Low Contrast ◽  
Contrast Structures ◽  
Scale Structures ◽  
Small Scale Structures ◽  
Coronal Structures

AbstractWe applied advanced image enhancement techniques to explore in detail the characteristics of the small-scale structures and/or the low contrast structures in several Coronal Mass Ejections (CMEs) observed by SOHO. We highlight here the results from our studies of the morphology and dynamical evolution of CME structures in the solar corona using two instruments on board SOHO: LASCO and EIT.

Image Enhancement in 26GHz-Band 1-Bit Direct Digital RF Transmitter Using Manchester Coding

2020 ◽  
Author(s):  
Junhao ZHANG ◽  
Masafumi KAZUNO ◽  
Mizuki MOTOYOSHI ◽  
Suguru KAMEDA ◽  
Noriharu SUEMATSU
Keyword(s):  
Image Enhancement ◽  
Rf Transmitter ◽  
Digital Rf ◽  
Manchester Coding

Deep-STRESS Capsule Video Endoscopy Image Enhancement

2018 ◽  
Vol 2018 (1) ◽  
pp. 247-252
Author(s):  
Ahmed Mohammed ◽  
Marius Pedersen ◽  
Øistein Hovde ◽  
Sule Yildirim
Keyword(s):  
Image Enhancement ◽  
Video Endoscopy

Colour Image Enhancement using Perceptual Saturation and Vividness

2019 ◽  
Vol 2019 (1) ◽  
pp. 243-246
Author(s):  
Muhammad Safdar ◽  
Noémie Pozzera ◽  
Jon Yngve Hardeberg
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Test Performance ◽  
Appearance Model ◽  
Colour Space ◽  
Categorical Judgment ◽  
Saturation Scale ◽  
Colour Image ◽  
Colour Appearance ◽  
Future Test

A perceptual study was conducted to enhance colour image quality in terms of naturalness and preference using perceptual scales of saturation and vividness. Saturation scale has been extensively used for this purpose while vividness has been little used. We used perceptual scales of a recently developed colour appearance model based on Jzazbz uniform colour space. A two-fold aim of the study was (i) to test performance of recently developed perceptual scales of saturation and vividness compared with previously used hypothetical models and (ii) to compare performance and chose one of saturation and vividness scales for colour image enhancement in future. Test images were first transformed to Jzazbz colour space and their saturation and vividness were then decreased or increased to obtain 6 different variants of the image. Categorical judgment method was used to judge preference and naturalness of different variants of the test images and results are reported.

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.

Sign in / Sign up

Export Citation Format

Share Document