Image contrast enhancement using triple clipped dynamic histogram equalisation based on standard deviation

Zarie, Majid; Pourmohammad, Ali; Hajghassem, Hassan

doi:10.1049/iet-ipr.2018.5395

Cited by 31 publications

(15 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various modifications to HE or histogram modification (HM) have been proposed to suppress over‐enhancement or compensate the detail information [2–21]. For example, local histogram equalization (LHE) methods separate the image into numbers sub‐blocks, then enhance these sub‐blocks individually, but these methods enhance both contrast and noises in local areas [4–6].…”

Section: Introductionmentioning

confidence: 99%

“…For example, local histogram equalization (LHE) methods separate the image into numbers sub‐blocks, then enhance these sub‐blocks individually, but these methods enhance both contrast and noises in local areas [4–6]. Bi‐histogram equalization (BHE) or multi‐histogram equalization (MHE)‐based methods separate the histogram into two or more parts based on certain conditions and then equalize them independently [7–11], including brightness preserving bi‐histogram equalization (BBHE) [7], minimum mean brightness error bi‐histogram equalization (MMBEBHE) [8], three adaptive sub‐histograms equalization (TASHE) [9], and so on. These methods alleviate the global over‐enhancement to some degree, but in each sub‐image, the over‐enhancement still exists.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A novel detail weighted histogram equalization method for brightness preserving image enhancement based on partial statistic and global mapping model

Yuan

Zheng

et al. 2022

IET Image Processing

View full text Add to dashboard Cite

Histogram equalization (HE) is a classic and widely used image contrast enhancement algorithm for its good performance and high efficiency. However, over‐enhancement caused by high peak in the histogram affects the subjective quality of the image processed by HE to a large extent. In this paper, a detail weighted histogram equalization (DWHE) method is proposed based on a novel histogram modification (HM) model named partial statistic and global mapping (PSGM) to alleviate high peak and suppress over‐enhancement. Moreover, the authors implement a refined version of gamma correction (GC) named texture enhancement function (TEF) on high‐frequency images to reduce the noise amplification effect. At last, the authors propose a novel adaptively weighted pixel‐level image fusion method to further reduce the phenomenon of over‐enhancement and improve brightness distribution. Both subjective and quantitative evaluations are conducted on images containing a variety of scenes. Compared with several state‐of‐the‐art image enhancement methods, the proposed framework obtained generally the best performance in aspects of both subjective appearance and objective evaluation indices. Therefore, it is proved that the proposed methods can effectively alleviate the over‐enhancement, enrich image details, and efficiently improve the visual quality while preserving the brightness of the image.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel detail weighted histogram equalization method for brightness preserving image enhancement based on partial statistic and global mapping model

Yuan

Zheng

et al. 2022

IET Image Processing

View full text Add to dashboard Cite

show abstract

“…A global and adaptive contrast enhancement algorithm for low illumination gray images reduces the uneven illumination and low overall contrast of gray image [10]. Also, triple partitioning of the histogram and histogram clipping is studied to control the enhancement ratio [26].…”

Section: Introductionmentioning

confidence: 99%

Enhancement of Region of Interest from a Single Backlit Image with Multiple Features

Yadav,

Mouli

2021

Communications in Computer and Information Science

View full text Add to dashboard Cite

Backlit images are a combination of dark and bright regions and the objects in the image generally appear to be dark for human perception. The region of interest (ROI) in general confines to the object(s) present in the image or some regions of the image. Such ROI in backlit images have low contrast and it is difficult for visualization. Enhancement of ROI in backlit images is necessary in order to view the contents properly. In this paper, a novel and simple approach for the enhancement of ROI of backlit images is proposed. This approach considers several features including tone mappings, exposedness, gradient, median filtering, etc. and finally, the fusion of the results has been done. The novel contribution in the proposed method, though seems to be trivial, attained best results without applying pyramid based operations namely Laplacian pyramid and Gaussian pyramid. Efficacy of the proposed method is evident from the experimental results which confirm that the proposed approach gives better results both qualitatively (visualization) and quantitatively (objective evaluation) compared to the existing methods.

show abstract

“…Each above-mentioned method is proposed to resolve a specific problem in the field of contrast enhancement. However, methods which could follow multiple targets are barely proposed [27][28]. In this paper, entropy-based triple dynamic clipped histogram equalization (ETDCHE) method is proposed.…”

Section: Introductionmentioning

confidence: 99%

Implementation of the electronic sector of the satellite camera and image contrast enhancement

Zarie

Khalilpour

Almaloo

2020

IJEECS

Self Cite

View full text Add to dashboard Cite

The purpose of this paper is to design and implement the electronic sector of satellite camera on the basis of systematic calculations as well as presenting the general and detailed block diagram. The main parts of the designed camera consist of four units named “optics, detector, processors, and memory” that can work in one of three modes: real-time, storage and storage-send. Verification of the simulation and practical results are shown completely by receiving images. According to the conditions of the satellite imaging, in most cases, there is a need to improve the image quality. A very important feature in the satellite images is contrast enhancement. In the following, a powerful contrast enhancement algorithm is proposed based on histogram equalization method called the “entropy-based triple dynamic clipped histogram equalization” (ETDCHE). One of the strengths of this paper is using images with diverse variations in brightness. Such that by producing clear images and by preserving maximum details this overcomes the adverse lighting conditions and leads to natural enhancement of the output images. Also, the performance assessment of the proposed method in terms of the average information content reflects the considerable superiority of the proposed algorithm compared to the previously presented methods based on histogram equalization.

show abstract

Image contrast enhancement using triple clipped dynamic histogram equalisation based on standard deviation

Cited by 31 publications

References 26 publications

A novel detail weighted histogram equalization method for brightness preserving image enhancement based on partial statistic and global mapping model

A novel detail weighted histogram equalization method for brightness preserving image enhancement based on partial statistic and global mapping model

Enhancement of Region of Interest from a Single Backlit Image with Multiple Features

Implementation of the electronic sector of the satellite camera and image contrast enhancement

Contact Info

Product

Resources

About