Automatic Exact Histogram Specification for Contrast Enhancement and Visual System Based Quantitative Evaluation

Sen, Debashis; Pal, Sankar K.

doi:10.1109/tip.2010.2083676

Cited by 75 publications

(39 citation statements)

References 21 publications

(64 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some renowned histogram specification-based methods such as automatic exact histogram specification (AEHS) [19] and dynamic histogram specification (DHS) [20] are available for image enhancement. AEHS is proposed for both local and global contrast enhancement whereas DHS uses differential information from an input histogram to eliminate the annoying side effects.…”

Section: Introductionmentioning

confidence: 99%

A histogram specification technique for dark image enhancement using a local transformation method

Hussain

Rahman

et al. 2018

IPSJ T Comput Vis Appl

View full text Add to dashboard Cite

Traditional image enhancement techniques produce different types of noise such as unnatural effects, over-enhancement, and artifacts, and these drawbacks become more prominent in enhancing dark images. To overcome these drawbacks, we propose a dark image enhancement technique where local transformation of the pixels have been performed. Here, we apply a transformation method of different parts of the histogram of an input image to get a desired histogram. Afterwards, histogram specification technique has been done on the input image using this transformed histogram. The performance of the proposed technique has been evaluated in both qualitative and quantitative manner, which shows that the proposed method improves the quality of the image with minimal unexpected artifacts as compared to the other techniques.

show abstract

Section: Introductionmentioning

confidence: 99%

A histogram specification technique for dark image enhancement using a local transformation method

Hussain

Rahman

et al. 2018

IPSJ T Comput Vis Appl

View full text Add to dashboard Cite

show abstract

“…There are also many histogram based techniques where the enhancement function is an S-type, or power, or logarithmic transform; see e.g. [25], [26], [27], [28], [19], among others. In particular, the approach in [26] is based on mathematical models for color perception and is automatic.…”

Section: Introductionmentioning

confidence: 99%

“…[25], [26], [27], [28], [19], among others. In particular, the approach in [26] is based on mathematical models for color perception and is automatic. Unfortunately, there is no clear algorithm nor tests on color images.…”

Section: Introductionmentioning

confidence: 99%

Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement

Nikolova

Steidl

2014

IEEE Trans. on Image Process.

View full text Add to dashboard Cite

“…Histogram processing is a technique with numerous applications, e.g., in invisible watermarking, image normalization and enhancement, object recognition [3], [5], [11], [13]. The goal of exact histogram specification (HS) is to transform an input image into an output image having a prescribed histogram.…”

Section: Introductionmentioning

confidence: 99%

Fast Ordering Algorithm for Exact Histogram Specification

Nikolova¹,

Steidl

2014

IEEE Trans. on Image Process.

View full text Add to dashboard Cite

This paper provides a fast algorithm to order in a strict way the integer gray values in digital images which can be applied for exact histogram specification. Our algorithm is based on the ordering procedure by the variational approach in [9]. This variational method was shown to be superior to other state-of-the art ordering algorithms in terms of faithful total strict ordering but not in speed. Indeed, the relevant functionals are in general difficult to minimize because their gradient is nearly flat over vast regions.In this paper we propose a simple and fast fixed point algorithm to minimize the functionals. The fast convergence of our algorithm results from known analytical properties of the model. In particular the original image is a good starting point for the iterations and the involved inverse functions admit a simple explicit form.Only a few iteration steps of this algorithm provide an image whose pixels can be ordered in a strict and faithful way. Numerical experiments confirm that our algorithm outperforms by far its main competitors in speed and quality. Moreover, in contrast to other ordering algorithms we can handle large images commonly taken by commercial cameras.Concerning applications the proposed ordering algorithm is the basis of the hue and range preserving color image enhancement method proposed in [11].

show abstract

Automatic Exact Histogram Specification for Contrast Enhancement and Visual System Based Quantitative Evaluation

Cited by 75 publications

References 21 publications

A histogram specification technique for dark image enhancement using a local transformation method

A histogram specification technique for dark image enhancement using a local transformation method

Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement

Fast Ordering Algorithm for Exact Histogram Specification

Contact Info

Product

Resources

About