scholarly journals Personal Communication Technologies for Smart Spaces Density-Based Clustering for Content and Color Adaptive Tone Mapping

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Maleeha Javed ◽  
Hassan Dawood ◽  
Muhammad Murtaza Khan ◽  
Ameen Banjar ◽  
Riad Alharbey ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Subjective Evaluation ◽  
Personal Communication ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Density Peak ◽  
Mapping Algorithm ◽  
Fast Search ◽  
And Performance ◽  
Low Dynamic Range

Tone mapping operators are designed to display high dynamic range (HDR) images on low dynamic range devices. Clustering-based content and color adaptive tone mapping algorithm aims to maintain the color information and local texture. However, fine details can still be lost in low dynamic range images. This paper presents an effective way of clustering-based content and color adaptive tone mapping algorithm by using fast search and find of density peak clustering. The suggested clustering method reduces the loss of local structure and allows better adaption of color in images. The experiments are carried out to evaluate the effectiveness and performance of proposed technique with state-of-the-art clustering techniques. The objective and subjective evaluation results reveal that fast search and find of density peak preserves more textural information. Therefore, it is most suitable to be used for clustering-based content and color adaptive tone mapping algorithm.

New segmentation-based tone mapping algorithm for high dynamic range image

2017 ◽  
Author(s):  
Weiwei Duan ◽  
Huinan Guo ◽  
Zuofeng Zhou ◽  
Huimin Huang ◽  
Jianzhong Cao
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Image ◽  
High Dynamic Range Image ◽  
Mapping Algorithm ◽  
High Dynamic

scholarly journals Inverse Tone Mapping Based upon Retina Response

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yongqing Huo ◽  
Fan Yang ◽  
Vincent Brost
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
High Quality ◽  
Physiological Approach ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
Image Details ◽  
Inverse Tone Mapping ◽  
Expansion Scheme

The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor. This paper proposed a novel physiological approach, which could avoid artifacts occurred in most existing algorithms. Inspired by the property of the human visual system (HVS), this dynamic range expansion scheme performs with a low computational complexity and a limited number of parameters and obtains high-quality HDR results. Comparisons with three recent algorithms in the literature also show that the proposed method reveals more important image details and produces less contrast loss and distortion.

scholarly journals Temporal adaptation control for local tone mapping operator

2018 ◽  
Vol 69 (4) ◽  
pp. 261-269
Author(s):  
Dragomir El Mezeni ◽  
Lazar Saranovac
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Temporal Control ◽  
Display Devices ◽  
Flexible Control ◽  
Temporal Adaptation ◽  
Single Operator ◽  
Low Dynamic Range ◽  
Local Tone Mapping

Abstract High dynamic range (HDR) imaging has gained great popularity over the past twenty years. Tone mapping operator (TMO) is the key component that enables reproduction of HDR images on the standard low dynamic range (LDR) display devices. When it comes to the HDR video, design of the TMO becomes especially challenging since temporal control of TMO parameters is needed in order to avoid possible artifacts. Since temporal and spatial contrast cannot be met simultaneously, existing solutions are usually designed to optimize one of these two requirements. We present novel local tone mapping operator that preserves details and simultaneously provides good local and global contrast of processed images. Tunable temporal control enables trade-off between spatial and temporal contrast of a tone mapped video. Flexible control presented in this paper ensures that both requirements can be met with a single operator just by using different tuning of the control block.When compared to the state-of-the-art TMOs, proposed solution exhibits better results regarding overall image quality.

scholarly journals K-means clustering based tone-mapping operator for high dynamic range video

2021 ◽  
Author(s):  
Negar Taherian
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Scene Change Detection ◽  
Mapping Algorithms ◽  
Mapping Algorithm ◽  
High Dynamic ◽  
Video Input

The field of high dynamic range (HDR) imaging deals with capturing the luminance of a natural scene, usually varying between 10−3 to 105 cd/m2 and displaying it on digital devices with much lower dynamic range. Here, we present a novel tone mapping algorithm that is based on K-means clustering. Our algorithm takes into account the color information within a frame and using k-means clustering algorithm it builds clusters on the intensities within an image and shifts the values within each cluster to a displayable dynamic range. We also implement a scene change detection to reduce the running time of our algorithm by using the cluster information from the previous frame for frames within the same scene. To reduce the flicker effect, we proposed a new method that multiplies a leaky integer to the centroid values of our clustering results. Our algorithm runs in O( N logK + K logK ) for an image with N input luminance levels and K output levels. We also show how to extend the method to handle video input. We display that our algorithm gives comparable results to state-of-the- art tone mapping algorithms. We test our algorithm on a number of standard high dynamic range images and video sequences and provide qualitative and quantitative comparisons to a number of state-of-the-art tone mapping algorithms for videos.

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