scholarly journals Fast Single-Image HDR Tone-Mapping by Avoiding Base Layer Extraction

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4378
Author(s):  
Masud An-Nur Islam Fahim ◽  
Ho Yub Jung
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Base Layer ◽  
Tone Mapping ◽  
Mapping Algorithm ◽  
Halo Effects ◽  
Adaptive Parameter ◽  
Gradient Domain ◽  
Layer Extraction ◽  
Saturation Effects

The tone-mapping algorithm compresses the high dynamic range (HDR) information into the standard dynamic range for regular devices. An ideal tone-mapping algorithm reproduces the HDR image without losing any vital information. The usual tone-mapping algorithms mostly deal with detail layer enhancement and gradient-domain manipulation with the help of a smoothing operator. However, these approaches often have to face challenges with over enhancement, halo effects, and over-saturation effects. To address these challenges, we propose a two-step solution to perform a tone-mapping operation using contrast enhancement. Our method improves the performance of the camera response model by utilizing the improved adaptive parameter selection and weight matrix extraction. Experiments show that our method performs reasonably well for overexposed and underexposed HDR images without producing any ringing or halo effects.

Efficient and Adaptive Tone Mapping Algorithm Based on Guided Image Filter

2019 ◽  
Vol 34 (04) ◽  
pp. 2054012 ◽  
Author(s):  
Yuan Jia ◽  
Wenting Zhang
Keyword(s):  
Dynamic Range ◽  
Recognition Rate ◽  
Objective Evaluation ◽  
High Dynamic Range ◽  
Base Layer ◽  
Tone Mapping ◽  
Image Filter ◽  
Mapping Algorithm ◽  
Guided Image Filter ◽  
Hdr Image

The recognition rate of computer vision algorithms is highly dependent on the image quality. To enhance the visual quality of the images captured under high-dynamic range (HDR) scenes, we propose an efficient and adaptive tone mapping algorithm based on guided image filter (GIF). The HDR image is compressed adaptively according to its average luminance. Then we decompose it into a base layer and a detail layer using the guided image filter. We improve the base layer and enhance the detail layer simultaneously, and combine the two layers to get the final low-dynamic range (LDR) image. Since the parameters are linked with image statistics, they adaptively fit to various kinds of images. The objective evaluation results on HDR image sets demonstrate the superiority of our proposed algorithm. Meanwhile, the result of our algorithm can reduce the halo artifacts and preserve more detail by subjective observation.

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 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.

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.

scholarly journals A Weighted Histogram-Based Tone Mapping Algorithm for CT Images

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 111 ◽  
Author(s):  
David Völgyes ◽  
Anne Martinsen ◽  
Arne Stray-Pedersen ◽  
Dag Waaler ◽  
Marius Pedersen
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Histogram Equalization ◽  
Ct Images ◽  
Tone Mapping ◽  
Local Contrast ◽  
Kernel Size ◽  
Mapping Algorithm ◽  
High Dynamic ◽  
Weighted Histogram

Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared to eight popular tone mapping operators.

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