Local Edge-Preserving Multiscale Decomposition for High Dynamic Range Image Tone Mapping

Gu, Bo; Li, Wujing; Zhu, Minyun; Wang, Minghui

doi:10.1109/tip.2012.2214047

Cited by 116 publications

(28 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the phase image can be decomposed as the background image and detail layer, the contrast of the latter is critical in display. Thus, in this study the 16-bit phase image I is separated into the background B and detail images by employing the edge preserving filter [ 19 ]. An objective function is established in the subset w.

where ɛ is a regularization parameter and ▽ is the gradient operator.…”

Section: Methodsmentioning

confidence: 99%

An Infrared Defect Sizing Method Based on Enhanced Phase Images

Wei

Mao

et al. 2020

Sensors

View full text Add to dashboard Cite

Infrared thermography (IRT) is a full-field, contactless technique that has been widely used for nondestructive evaluation of structural materials due to many advantages. One of the major limitations of IRT is the fuzzy edge and low contrast in the inspected images—as well as the cost of the system. An efficient image post-processing with an affordable and portable device is of great interest to the engineering society. In this study, a convenient and economical inspection system using common halogen lamps was constructed. The corresponding image-processing scheme, which includes Fourier phase analysis and specific image enhancement was developed to identify defects with sharp and clear edges and good contrast. This system was applied to localized of defects in glass-fiber-reinforced composite panels. The results showed that defects with an effective diameter as small as 5 mm can be detected with excellent image quality. As a conclusion, the developed system provides an economic alternative to traditional infrared thermography which is able to identify defects with good qualities.

show abstract

where ɛ is a regularization parameter and ▽ is the gradient operator.…”

Section: Methodsmentioning

confidence: 99%

An Infrared Defect Sizing Method Based on Enhanced Phase Images

Wei

Mao

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Figure 3 shows that image of the red channel exhibits the best contrast for separating epithelium from connective tissue. Figure 4 is the smoothed red image with edge-preserving decomposition [9], which generated an image with less noise and it is easy to binarize. Next, global thresholding was applied on the smoothed red image to obtain the mask of the epithelial layer.…”

Section: Methodsmentioning

confidence: 99%

Quantitative diagnosis of tongue cancer from histological images in an animal model

Qin

Wang

et al. 2016

SPIE Proceedings

View full text Add to dashboard Cite

We developed a chemically-induced oral cancer animal model and a computer aided method for tongue cancer diagnosis. The animal model allows us to monitor the progress of the lesions over time. Tongue tissue dissected from mice was sent for histological processing. Representative areas of hematoxylin and eosin (H&E) stained tissue from tongue sections were captured for classifying tumor and non-tumor tissue. The image set used in this paper consisted of 214 color images (114 tumor and 100 normal tissue samples). A total of 738 color, texture, morphometry and topology features were extracted from the histological images. The combination of image features from epithelium tissue and its constituent nuclei and cytoplasm has been demonstrated to improve the classification results. With ten iteration nested cross validation, the method achieved an average sensitivity of 96.5% and a specificity of 99% for tongue cancer detection. The next step of this research is to apply this approach to human tissue for computer aided diagnosis of tongue cancer.

show abstract

“…Local-based photographic reproduction methods yield suitable transfer functions for individual pixels. Gu et al [ 11 ] proposed three assumptions and designed a local edge-preserving filter that avoids gradient reversal to perform multiscale decomposition of images. Barai et al [ 12 ] integrated a saliency map with the edge-preserving guided filter and also enhanced the detail layer that is rich in edge information.…”

Section: Related Work and Research Motivationmentioning

confidence: 99%

Photographic Reproduction and Enhancement Using HVS-Based Modified Histogram Equalization

Chen

Hua

Tsai

et al. 2021

Sensors

View full text Add to dashboard Cite

Photographic reproduction and enhancement is challenging because it requires the preservation of all the visual information during the compression of the dynamic range of the input image. This paper presents a cascaded-architecture-type reproduction method that can simultaneously enhance local details and retain the naturalness of original global contrast. In the pre-processing stage, in addition to using a multiscale detail injection scheme to enhance the local details, the Stevens effect is considered for adapting different luminance levels and normally compressing the global feature. We propose a modified histogram equalization method in the reproduction stage, where individual histogram bin widths are first adjusted according to the property of overall image content. In addition, the human visual system (HVS) is considered so that a luminance-aware threshold can be used to control the maximum permissible width of each bin. Then, the global tone is modified by performing histogram equalization on the output modified histogram. Experimental results indicate that the proposed method can outperform the five state-of-the-art methods in terms of visual comparisons and several objective image quality evaluations.

show abstract

Local Edge-Preserving Multiscale Decomposition for High Dynamic Range Image Tone Mapping

Cited by 116 publications

References 20 publications

An Infrared Defect Sizing Method Based on Enhanced Phase Images

An Infrared Defect Sizing Method Based on Enhanced Phase Images

Quantitative diagnosis of tongue cancer from histological images in an animal model

Photographic Reproduction and Enhancement Using HVS-Based Modified Histogram Equalization

Contact Info

Product

Resources

About