Metal-dielectric photonic devices for spatial filtering and image contrast enhancement

2013 ◽  
Author(s):  
Anna Pastuszczak ◽  
Piotr Wróbel ◽  
Tomasz Stefaniuk ◽  
Marcin Stolarek ◽  
Mateusz Wlazło ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Spatial Filtering ◽  
Photonic Devices ◽  
Image Contrast ◽  
Image Contrast Enhancement

scholarly journals Terahertz Spiral Spatial Filtering Imaging

2021 ◽  
Vol 11 (6) ◽  
pp. 2526
Author(s):  
Hui Liu ◽  
Shiyou Wu ◽  
Meng Zhao ◽  
Chao Li ◽  
XiaoJun Liu ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Imaging System ◽  
Spatial Filtering ◽  
Spatial Spectrum ◽  
Image Contrast ◽  
Phase Plate ◽  
Imaging Method ◽  
Fourier Plane ◽  
Image Contrast Enhancement ◽  
Spiral Phase

In this paper, we propose a terahertz (THz) spiral spatial filtering (SSF) imaging method that can enable image contrast enhancement. The related theory includes three main steps: (1) the THz image of the target is Fourier transformed to the spatial spectrum distribution; (2) the spatial spectrum is modulated by a spiral phase at the Fourier plane; (3) the filtered spatial spectrum is inverse Fourier transformed to the desired THz image. Meanwhile, analytic expression of the final THz image is derived. Due to the unique nature of the spiral phase, THz image contrast enhancement can be achieved and verified by various simulated target images with different contrasts. In our designed THz SSF imaging system, Fourier transform is carried out by the lens, and the spiral phase is acquired by the spiral phase plate (SPP). Proof-of-principle experiments with three different types of targets (carved metal letters, a high-density polyethylene (HDPE) piece with a scratch, and a leaf) were carried out, and the effectiveness of contrast enhancement and edge extraction on the THz reconstruction images was validated.

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.

Ceed - A Database for Image Contrast Enhancement Evaluation

2018 ◽  
Author(s):  
Azeddine Beghdadi ◽  
Muhammad Ali Qureshi ◽  
Bilel Sdiri ◽  
Mohamed Deriche ◽  
Faouzi Alaya-Cheikh
Keyword(s):  
Contrast Enhancement ◽  
Image Contrast ◽  
Image Contrast Enhancement
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