Assessment of light source bandwidth impacts on image contrast enhancement using process window discovery

2017 ◽  
Author(s):  
Paolo Alagna ◽  
Greg Rechtsteiner ◽  
Will Conley ◽  
Andrew Cross ◽  
Kaushik Sah ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Light Source ◽  
Image Contrast ◽  
Process Window ◽  
Image Contrast Enhancement

Image contrast enhancement of multiple patterning features through lower light source bandwidth

2017 ◽  
Author(s):  
Paolo Alagna ◽  
Will Conley ◽  
Greg Rechtsteiner ◽  
Kathleen Nafus ◽  
Serge Biesemans
Keyword(s):  
Contrast Enhancement ◽  
Light Source ◽  
Image Contrast ◽  
Image Contrast Enhancement ◽  
Lower Light

scholarly journals Spectrally tunable light source based on a digital micromirror device for retinal image contrast enhancement

2015 ◽  
Vol 55 (3) ◽  
Author(s):  
Piotr Bartczak ◽  
Daiga Čerāne ◽  
Pauli Fält ◽  
Pasi Ylitepsa ◽  
Elina Hietanen ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Light Source ◽  
Retinal Image ◽  
Image Contrast ◽  
Image Feature ◽  
Optical Methods ◽  
Digital Micromirror Device ◽  
Artificial Eye ◽  
Image Contrast Enhancement

Different optical methods for retinal imaging provide a significant improvement for image analysis and help with data interpretation. The use of tunable light sources, which have been optimized for contrast enhancement of various retinal features or lesions in retinal images, could simplify the eye fundus examination through enhanced image quality. In this study, we have developed and described a research prototype which consists of a spectrally tunable light source based on a digital micromirror device which is further coupled to a fundus camera. The overall aim of this construction was to generate illuminations optimized for enhanced retinal image feature visibility. The optimized illumination conditions were compared to traditional red-free imaging and the measurements were executed for an artificial eye followed by in vivo measurements of the eyes of three volunteers. In all cases, the retinal image contrast was observed to improve compared to the traditional red-free imaging. Depending on the observed retinal feature, the perceptual improvements in the contrast varied from a few percent to nearly 70 percent.

DCT Coefficients Weighting (DCTCW)-Based Gray Wolf Optimization (GWO) for Brightness Preserving Image Contrast Enhancement

2021 ◽  
Author(s):  
Saorabh Kumar Mondal ◽  
Arpitam Chatterjee ◽  
Bipan Tudu
Keyword(s):  
Contrast Enhancement ◽  
Objective Evaluation ◽  
Brightness Distribution ◽  
Image Contrast ◽  
Optimization Techniques ◽  
Biological Behavior ◽  
Gray Wolf ◽  
Original Image ◽  
Image Characteristics ◽  
Image Contrast Enhancement

Image contrast enhancement (CE) is a frequent image enhancement requirement in diverse applications. Histogram equalization (HE), in its conventional and different further improved ways, is a popular technique to enhance the image contrast. The conventional as well as many of the later versions of HE algorithms often cause loss of original image characteristics particularly brightness distribution of original image that results artificial appearance and feature loss in the enhanced image. Discrete Cosine Transform (DCT) coefficient mapping is one of the recent methods to minimize such problems while enhancing the image contrast. Tuning of DCT parameters plays a crucial role towards avoiding the saturations of pixel values. Optimization can be a possible solution to address this problem and generate contrast enhanced image preserving the desired original image characteristics. Biological behavior-inspired optimization techniques have shown remarkable betterment over conventional optimization techniques in different complex engineering problems. Gray wolf optimization (GWO) is a comparatively new algorithm in this domain that has shown promising potential. The objective function has been formulated using different parameters to retain original image characteristics. The objective evaluation against CEF, PCQI, FSIM, BRISQUE and NIQE with test images from three standard databases, namely, SIPI, TID and CSIQ shows that the presented method can result in values up to 1.4, 1.4, 0.94, 19 and 4.18, respectively, for the stated metrics which are competitive to the reported conventional and improved techniques. This paper can be considered a first-time application of GWO towards DCT-based image CE.

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