scholarly journals Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification

2019 ◽  
Vol 11 (7) ◽  
pp. 849 ◽  
Author(s):  
Chengwei Liu ◽  
Xiubao Sui ◽  
Xiaodong Kuang ◽  
Yuan Liu ◽  
Guohua Gu ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Visual Quality ◽  
Local Contrast ◽  
Original Image ◽  
Infrared Images ◽  
Histogram Specification ◽  
Block Based ◽  
Global And Local ◽  
2D Histogram

In this paper, an optimized contrast enhancement method combining global and local enhancement results is proposed to improve the visual quality of infrared images. Global and local contrast enhancement methods have their merits and demerits, respectively. The proposed method utilizes the complementary characteristics of these two methods to achieve noticeable contrast enhancement without artifacts. In our proposed method, the 2D histogram, which contains both global and local gray level distribution characteristics of the original image, is computed first. Then, based on the 2D histogram, the global and local enhanced results are obtained by applying histogram specification globally and locally. Lastly, the enhanced result is computed by solving an optimization equation subjected to global and local constraints. The pixel-wise regularization parameters for the optimization equation are adaptively determined based on the edge information of the original image. Thus, the proposed method is able to enhance the local contrast while preserving the naturalness of the original image. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms the block-based methods for improving the visual quality of infrared images.

scholarly journals Adaptive Contrast Enhancement for Infrared Images Based on the Neighborhood Conditional Histogram

2019 ◽  
Vol 11 (11) ◽  
pp. 1381 ◽  
Author(s):  
Chengwei Liu ◽  
Xiubao Sui ◽  
Xiaodong Kuang ◽  
Yuan Liu ◽  
Guohua Gu ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Noise Suppression ◽  
Mapping Function ◽  
Visual Quality ◽  
Histogram Equalization ◽  
The Other ◽  
Local Contrast ◽  
Infrared Images ◽  
Local Contrast Enhancement ◽  
Block Based

In this paper, an adaptive contrast enhancement method based on the neighborhood conditional histogram is proposed to improve the visual quality of thermal infrared images. Existing block-based local contrast enhancement methods usually suffer from the over-enhancement of smooth regions or the loss of some details. To address these drawbacks, we first introduce a neighborhood conditional histogram to adaptively enhance the contrast and avoid the over-enhancement caused by the original histogram. Then the clip-redistributed histogram of the contrast-limited adaptive histogram equalization (CLAHE) is replaced by the neighborhood conditional histogram. In addition, the local mapping function of each sub-block is updated based on the global mapping function to further eliminate the block artifacts. Lastly, the optimized local contrast enhancement process, which combines both global and local enhanced results is employed to obtain the desired enhanced result. Experiments are conducted to evaluate the performance of the proposed method and the other five methods are introduced as a comparison. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms the other block-based methods on local contrast enhancement, visual quality improvement, and noise suppression.

An Efficient Adaptive Algorithm for Electron Microscopic Image Enhancement and Feature Extraction

2019 ◽  
Vol 9 (1) ◽  
pp. 1-16
Author(s):  
Vivek Arya ◽  
Vipul Sharma ◽  
Garima Arya
Keyword(s):  
Feature Extraction ◽  
Contrast Enhancement ◽  
Block Size ◽  
Sigmoid Function ◽  
Microscopic Image ◽  
Electron Microscopic ◽  
Microscopic Images ◽  
Electron Microscopic Image ◽  
Block Based

In this article, a block-based adaptive contrast enhancement algorithm has been proposed, which uses a modified sigmoid function for the enhancement and features extraction of electron microscopic images. The algorithm is based on a modified sigmoid function that adapts according to the input microscopic image statistics. For feature extraction, the contrast of the image is very important and authentic property by which this article enhances the visual quality of the image. In this work, for better contrast enhancement of image, a block based on input value, combined with a modified sigmoid function that is used as contrast enhancer provides better EMF values for a smaller block size. It provides localized contrast enhancement effects adaptively which is not possible using other existing techniques. Simulation and experimental results demonstrate that the proposed technique gives better results compared to other existing techniques when applied to electron microscopic images. After the enhancement of microscopic images of actinomycetes, various important features are shown, like coil or spiral, long filament, spore and rod shape structures. The proposed algorithm works efficiently for different dark and bright microscopic images.

scholarly journals Full Reference-Image Quality Assessment with Global and Local Image Regions for Visual Quality Perception and Optimization

2019 ◽  
Vol 8 (6S4) ◽  
pp. 352-356
Keyword(s):  
Quality Assessment ◽  
Image Quality Assessment ◽  
Optimization Problems ◽  
Visual Quality ◽  
Reference Image ◽  
Mathematical Methods ◽  
Mathematical Properties ◽  
Global And Local ◽  
Local Image

Quality Assessment (IQA) by using mathematical methods is offering favorable results in calculating visual quality of distorted images. These methods are developed by examining effective features that are compatible with characteristics of Human Visual System (HVS). But many of those methods are difficult to apply for optimization problems. This paper presents DCT based metric with easy implementation and having mathematical properties like differentiability, convexity and valid distance metricability to overcome the optimization problems. By using this method we are able to calculate the quality of image as a whole as well as the quality of local image regions.

Block-Based High Capacity Multilevel Image Steganography

2016 ◽  
Vol 25 (08) ◽  
pp. 1650091 ◽  
Author(s):  
Geeta Kasana ◽  
Kulbir Singh ◽  
Satvinder Singh Bhatia
Keyword(s):  
Digital Images ◽  
High Capacity ◽  
Block Size ◽  
Visual Quality ◽  
Cover Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Block Based ◽  
High Embedding Capacity

This paper proposes a block-based high capacity steganography technique for digital images. The cover image is decomposed into blocks of equal size and the largest pixel of each block is found to embed the secret data bits and also the smallest pixel of each block is used for embedding to enhance the capacity. Embedding of secret data is performed using the concept that the pixel of a cover image has only two states — even and odd. Multilevel approach is also combined in the proposed technique to achieve high embedding capacity. In order to make the proposed technique more secure, a key is generated using embedding levels, block size, pixel embedding way, encryption parameters, and starting blocks of each embedding levels. Embedding capacity and visual quality of stego images generated by the proposed steganography technique are higher than the existing techniques. Steganalysis tests have been performed to show the un-detectability and imperceptibility of the proposed technique.

scholarly journals Adaptive Multi-Scale Entropy Fusion De-Hazing Based on Fractional Order

2018 ◽  
Vol 4 (9) ◽  
pp. 108 ◽  
Author(s):  
Uche Nnolim
Keyword(s):  
Contrast Enhancement ◽  
Fractional Order ◽  
Local Contrast ◽  
Multi Scale ◽  
Fully Adaptive ◽  
Color Degradation ◽  
Fractional Filter ◽  
Global And Local ◽  
Enhancement Algorithm ◽  
Experimental Comparisons

This paper describes a proposed fractional filter-based multi-scale underwater and hazy image enhancement algorithm. The proposed system combines a modified global contrast operator with fractional order-based multi-scale filters used to generate several images, which are fused based on entropy and standard deviation. The multi-scale-global enhancement technique enables fully adaptive and controlled color correction and contrast enhancement without over exposure of highlights when processing hazy and underwater images. This in addition to the illumination/reflectance estimation coupled with global and local contrast enhancement. The proposed algorithm is also compared with the most recent available state-of-the-art multi-scale fusion de-hazing algorithm. Experimental comparisons indicate that the proposed approach yields a better edge and contrast enhancement results without a halo effect, without color degradation, and is faster and more adaptive than all other algorithms from the literature.

scholarly journals An Efficient Watermarking and Key Generation Technique Using DWT Algorithm in Three-Dimensional Image

2019 ◽  
Vol 8 (2) ◽  
pp. 2360-2365
Keyword(s):  
Low Frequency ◽  
Visual Quality ◽  
Huffman Coding ◽  
Secret Message ◽  
Source Image ◽  
Discrete Wavelet ◽  
Original Image ◽  
Least Significant Bit ◽  
Image Contrast Enhancement

Discrete Wavelet Transform is the algorithm which can be used to increase the contrast of an image for better visual quality of an image. The histogram value for original image with highest bins is taken for embedding the data into an image to perform the histogram equalization for repeating the process simultaneously. Information can be embedded into the source image with some bit value, for recovering the original image without any loss of the pixels. DWT is the first algorithm which has achieved the image contrast enhancement accurately. This approach maintained the original visual quality of an image even though themessage bits are embedded into the contrast-enhanced images. The proposed work with an original watermarking scheme based on the least significant bit technique. As a substitute of embedding the data into a simple image as watermarking, least significant bitmethod by utilizing the three wavelets transform is applied in the proposed system in order to enhance the embedding technique using spatial domain. For security, the Huffman coding has used to secure the data embedded into a host image, which can convert the secret message sequence into bit sequence for least significant bit operation. DWT can analyze the signal at multiple resolutions and it can divide the image into two types of quadrants as high and low-frequency quadrants. Here dividing an image into low and high it makes the information to hide.

scholarly journals Contrast enhancement of infrared images using Adaptive Histogram Equalization (AHE) with Contrast Limited Adaptive Histogram Equalization (CLAHE)

2018 ◽  
Vol 16 (37) ◽  
pp. 127-135
Author(s):  
Loay Kadom Abood
Keyword(s):  
Contrast Enhancement ◽  
Infrared Imaging ◽  
Experimental Tests ◽  
Histogram Equalization ◽  
Night Vision ◽  
Infrared Images ◽  
Adaptive Histogram Equalization ◽  
General Quality ◽  
Improvement Procedures

The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed significant improvements.

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