Enhancement of Eyeround Images Based on an Improved Fuzzy Algorithm

1999 ◽  
Vol 3 (6) ◽  
pp. 441-445
Author(s):  
Yaming Wang ◽  
◽  
Jiajun Wang ◽  
Yuanmei Wang ◽  
Yude Dong ◽  
...  
Keyword(s):  
Image Quality ◽  
Processing Speed ◽  
Information Loss ◽  
Fuzzy Algorithm ◽  
Fuzzy Enhancement ◽  
Enhancement Algorithm

Eye ground images are complex, with many details and uncertainties. Conventional enhancement algorithms do not enhance these images suitably of inferior processing. S. K. Pal proposed a fuzzy enhancement algorithm with advantages, but these were compromised by slow processing and information loss. We propose a fuzzy enhancement algorithm for eyeground images introducing mapping and implementing the algorithm through table searches, significantly improving image quality and processing speed.

FPGA Implementation of Real-Time Adaptive Bidirectional Equalization for Histogram

2012 ◽  
Vol 461 ◽  
pp. 215-219
Author(s):  
Yu Qian Zhao ◽  
Zhi Gang Li
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Processing Speed ◽  
Local Maximum ◽  
Histogram Equalization ◽  
Infrared Images ◽  
Single Frame ◽  
Processing Effects ◽  
Simulation Results ◽  
Enhancement Algorithm

According to the characteristics of infrared images, a contrast enhancement algorithm was presented. The principium of FPGA-based adaptive bidirectional plateau histogram equalization was given in this paper. The plateau value was obtained by finding local maximum and whole maximum in statistical histogram based on dimensional histogram statistic. Statistical histogram was modified by the plateau value and balanced in gray scale and gray spacing. Test data generated by single frame image, which was simulated by FPGA-based real-time adaptive bidirectional plateau histogram equalization. The simulation results indicates that the precept meet the requests well in both the image processing effects and processing speed

scholarly journals Image Enhancement for Inspection of Cable Images Based on Retinex Theory and Fuzzy Enhancement Method in Wavelet Domain

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 570 ◽  
Author(s):  
Xuhui Ye ◽  
Gongping Wu ◽  
Le Huang ◽  
Fei Fan ◽  
Yongxiang Zhang
Keyword(s):  
Image Quality ◽  
Power Transmission ◽  
Low Frequency ◽  
Speckle Noise ◽  
Standard Test ◽  
Low Contrast ◽  
Inspection Robot ◽  
Fuzzy Enhancement ◽  
Enhancement Method ◽  
Frequency Components

Inspection images of power transmission line provide vision interaction for the operator and the environmental perception for the cable inspection robot (CIR). However, inspection images are always contaminated by severe outdoor working conditions such as uneven illumination, low contrast, and speckle noise. Therefore, this paper proposes a novel method based on Retinex and fuzzy enhancement to improve the image quality of the inspection images. A modified multi-scale Retinex (MSR) is proposed to compensate the uneven illumination by processing the low frequency components after wavelet decomposition. Besides, a fuzzy enhancement method is proposed to perfect the edge information and improve contrast by processing the high frequency components. A noise reduction procedure based on soft threshold is used to avoid the noise amplification. Experiments on the self-built standard test dataset show that the algorithm can improve the image quality by 3–4 times. Compared with several other methods, the experimental results demonstrate that the proposed method can obtain better enhancement performance with more homogeneous illumination and higher contrast. Further research will focus on improving the real-time performance and parameter adaptation of the algorithm.

The VLSI Design of Fingerprint Normalization Algorithm

2010 ◽  
Vol 29-32 ◽  
pp. 2428-2434
Author(s):  
Shi Min Du
Keyword(s):  
Image Quality ◽  
Basic Principle ◽  
Vlsi Design ◽  
Fingerprint Identification ◽  
Fingerprint Image ◽  
Fingerprint Enhancement ◽  
Enhancement Algorithm

Fingerprint identification is one of the most important biometric technologies, which has drawn a substantial amount of attention recently. Fingerprint enhancement algorithm is an important component of fingerprint identification. Normalization is the first step of enhancement algorithm. In this paper, the VLSI design of normalization algorithm is proposed. This paper performs these following tasks. Firstly, the flow of enhancement algorithm and the basic principle of normalization algorithm is introduced. Then, a scheme of VLSI design of normalization algorithm is proposed and described in detail. Finally, we implement this design with Verilog language and present the simulation result with Modesim9.0. The simulation result shows that the scheme proposed in this paper has improved the fingerprint image quality to a certain extent.

scholarly journals Adaptive Smoothness Constraint Image Multilevel Fuzzy Enhancement Algorithm

2019 ◽  
Vol 48 (12) ◽  
pp. 2777-2785 ◽  
Author(s):  
Xi Chu ◽  
Zhixiang Zhou ◽  
Chaoshan Yang ◽  
Xiaoju Xiang
Keyword(s):  
Fuzzy Enhancement ◽  
Smoothness Constraint ◽  
Enhancement Algorithm

Automatic Airport Extraction Based on Improved Fuzzy Enhancement

2011 ◽  
Vol 130-134 ◽  
pp. 3421-3424
Author(s):  
Li Pan ◽  
Zhao Xian Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Image Enhancement ◽  
High Speed ◽  
Good Effect ◽  
Remote Sensing Images ◽  
Fuzzy Enhancement ◽  
Region Labeling ◽  
Strong Robustness ◽  
Enhancement Algorithm

We put forward a process of automatic airport extraction based on the characteristics of high resolution remote sensing images. First, through image enhancement algorithm, the contrast of target and background is enhanced. Second, we can extract the possible airport through the algorithms of Ostu segmentation, mathematical morphology corrosion and region-labeling. Finally, combined with the geometric structure of the runway, the airfield runway can be extracted through the algorithms of edge detection, progressive probability Hough transform and line connection. Then the possible airport can be verified by the extracted airfield runway. In the process, we proposed an improved fuzzy enhancement algorithm for image enhancement. This algorithm has good effect on the image enhancement and has strong robustness. The results of the experiment indicate that the process of automatic airport extraction is robust and has the advantages of high speed and degree of automation.

Application of Adaptive Enhancement Means in Head and Neck CR Image

2012 ◽  
Vol 236-237 ◽  
pp. 409-413
Author(s):  
Ming Hui Zhang ◽  
Yao Yu Zhang
Keyword(s):  
Soft Tissue ◽  
Image Quality ◽  
Radiation Dose ◽  
Head And Neck ◽  
Clinical Diagnosis ◽  
Visual Effect ◽  
X Ray ◽  
Unsharp Masking ◽  
Adaptive Enhancement ◽  
Enhancement Algorithm

Digital CR of head and neck overcomes the disadvantage of regular X-ray radiography, which can not reveal bone and soft tissue position deficiency in one exposing, and reduces the X-ray radiation dose. Meanwhile, various factors cause the decline of image quality, and images must be enhanced in order to meet demands of doctor's clinical diagnosis. The general enhancement algorithms don’t consider body's structure differences and density characteristics. A new adaptive CR enhancement algorithm was proposed in this article, and head and neck CR images were processed with this method and compared with linear unsharp masking method. The experiment proves that the details of CR image enhanced were abundant and enhanced CR image had good visual effect, SNR was high, as well as detail variance /background variance (DV/BV) indicating that this algorithm is suitable for head and neck CR medical images

A bilinear fast fuzzy enhancement algorithm for image boundary detection

2018 ◽  
Vol 35 (4) ◽  
pp. 4083-4095
Author(s):  
Qulin Tan ◽  
Xiaopei Cai ◽  
Xiaochun Qin ◽  
Jiping Hu ◽  
G. de Oliveira
Keyword(s):  
Boundary Detection ◽  
Fuzzy Enhancement ◽  
Enhancement Algorithm

scholarly journals Classical and Fuzzy Based Image Enhancement Techniques for Banana Root Disease Diagnosis: A Review and Validation

2020 ◽  
Vol 13 (1) ◽  
pp. 50-62
Author(s):  
D. Suryaprabha ◽  
J. Satheeshkumar ◽  
N. Seenivasan
Keyword(s):  
Image Quality ◽  
Frequency Domain ◽  
Image Enhancement ◽  
Plant Root ◽  
Histogram Equalization ◽  
Disease Diagnosis ◽  
Root Disease ◽  
Classical Point ◽  
Enhancement Algorithm

A vital step in automation of plant root disease diagnosis is to extract root region from the input images in an automatic and consistent manner. However, performance of segmentation algorithm over root images directly depends on the quality of input images. During acquisition, the captured root images are distorted by numerous external factors like lighting conditions, dust and so on. Hence it is essential to incorporate an image enhancement algorithm as a pre-processing step in the plant root disease diagnosis module. Image quality can be improved either by manipulating the pixels through spatial or frequency domain. In spatial domain, images are directly manipulated using their pixel values and alternatively in frequency domain, images are indirectly manipulated using transformations. Spatial based enhancement methods are considered as favourable approach for real time root images as it is simple and easy to understand with low computational complexity. In this study, real time banana root images were enhanced by attempting with different spatial based image enhancement techniques. Different classical point processing methods (contrast stretching, logarithmic transformation, power law transformation, histogram equalization, adaptive histogram equalization and histogram matching) and fuzzy based enhancement methods using fuzzy intensification operator and fuzzy if-then rule based methods were tried to enhance the banana root images. Quality of the enhanced root images obtained through different classical point processing and fuzzy based methods were measured using no-reference image quality metrics, entropy and blind image quality index. Hence, this study concludes that fuzzy based method could be deployed as a suitable image enhancement algorithm while devising the image processing modules for banana root disease diagnosis.

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