Human Visual System-Based Saliency Detection for High Dynamic Range Content

2016 ◽  
Vol 18 (4) ◽  
pp. 549-562 ◽  
Author(s):  
Yuanyuan Dong ◽  
Mahsa T. Pourazad ◽  
Panos Nasiopoulos
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Dynamic Range ◽  
Saliency Detection ◽  
High Dynamic Range ◽  
High Dynamic

scholarly journals Human visual system inspired saliency guided edge preserving tone-mapping for high dynamic range imaging

2021 ◽  
Author(s):  
Nipu Rani Barai
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Guided Filter ◽  
Tone Mapping ◽  
High Dynamic Range Imaging ◽  
Range Imaging ◽  
Edge Preserving ◽  
High Dynamic

With the growing popularity of High Dynamic Range Imaging (HDRI), the necessity for advanced tone-mapping techniques has greatly increased. In this thesis, I propose a novel saliency guided edge-preserving tone-mapping method that uses saliency region information of an HDR image as input to a guided filter for base and detail image layer separation. Both high resolution and low resolution saliency maps were used for the performance evaluation of the proposed method. After detail layer enhancement and base layer compression with constant weights, a new edge preserved tone-mapped image was composed by adding the layers back together with saturation and exposure adjustments. The filter operation is faster due to the use of the guided filter, which has O(N) time operation with N number of pixels. Both objective and subjective quality assessment results demonstrated that the proposed method has higher edge and naturalness preserving capability, which is homologous to the Human Visual System (HVS), as compared to other state-of-the-art tone-mapping approaches.

scholarly journals Human visual system inspired saliency guided edge preserving tone-mapping for high dynamic range imaging

2021 ◽  
Author(s):  
Nipu Rani Barai
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Guided Filter ◽  
Tone Mapping ◽  
High Dynamic Range Imaging ◽  
Range Imaging ◽  
Edge Preserving ◽  
High Dynamic

With the growing popularity of High Dynamic Range Imaging (HDRI), the necessity for advanced tone-mapping techniques has greatly increased. In this thesis, I propose a novel saliency guided edge-preserving tone-mapping method that uses saliency region information of an HDR image as input to a guided filter for base and detail image layer separation. Both high resolution and low resolution saliency maps were used for the performance evaluation of the proposed method. After detail layer enhancement and base layer compression with constant weights, a new edge preserved tone-mapped image was composed by adding the layers back together with saturation and exposure adjustments. The filter operation is faster due to the use of the guided filter, which has O(N) time operation with N number of pixels. Both objective and subjective quality assessment results demonstrated that the proposed method has higher edge and naturalness preserving capability, which is homologous to the Human Visual System (HVS), as compared to other state-of-the-art tone-mapping approaches.

scholarly journals Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging

2020 ◽  
Vol 10 (7) ◽  
pp. 2513 ◽  
Author(s):  
Hyuk-Ju Kwon ◽  
Sung-Hak Lee
Keyword(s):  
Image Quality ◽  
Contrast Sensitivity ◽  
Human Visual System ◽  
Dynamic Range ◽  
Bilateral Filter ◽  
High Dynamic Range ◽  
Sensitivity Function ◽  
Base Layer ◽  
Compensation Technique ◽  
High Dynamic

High dynamic range (HDR) imaging is used to represent scenes with a greater dynamic range of luminance on a standard dynamic range display. Usually, HDR images are synthesized through base–detail separations. The base layer is used for tone compression and the detail layer is used for detail preservation. The representative detail-preserved algorithm iCAM06 has a tendency to reduce the sharpness of dim surround images, because of the fixed edge-stopping function of the fast-bilateral filter (FBF). This paper proposes a novel base–detail separation and detail compensation technique using the contrast sensitivity function (CSF) in the segmented frequency domain. Experimental results show that the proposed rendering method has better sharpness features and image quality than previous methods correlated by the human visual system.

scholarly journals Perceptually motivated model for predicting banding artefacts in high-dynamic range images

2020 ◽  
Vol 2020 (28) ◽  
pp. 42-48
Author(s):  
Minjung Kim ◽  
Maryam Azimi ◽  
Rafał K. Mantiuk
Keyword(s):  
Visual System ◽  
Contrast Sensitivity ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Sensitivity Function ◽  
Psychophysical Experiment ◽  
Texture Region ◽  
Wide Range ◽  
Artefact Detection ◽  
High Dynamic

Banding is a type of quantisation artefact that appears when a low-texture region of an image is coded with insufficient bitdepth. Banding artefacts are well-studied for standard dynamic range (SDR), but are not well-understood for high dynamic range (HDR). To address this issue, we conducted a psychophysical experiment to characterise how well human observers see banding artefacts across a wide range of luminances (0.1 cd/m2–10,000 cd/m2). The stimuli were gradients modulated along three colour directions: black-white, red-green, and yellow-violet. The visibility threshold for banding artefacts was the highest at 0.1 cd/m2, decreased with increasing luminance up to 100 cd/m2, then remained at the same level up to 10,000 cd/m2. We used the results to develop and validate a model of banding artefact detection. The model relies on the contrast sensitivity function (CSF) of the visual system, and hence, predicts the visibility of banding artefacts in a perceptually accurate way.

scholarly journals Protuberancy State Recognition in Human Visual System

2020 ◽  
pp. 423-425
Author(s):  
Bharath V ◽  
Jeba N ◽  
Priyadharshini P ◽  
Gurur raja
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Dynamic Range ◽  
Visual Saliency ◽  
High Dynamic Range ◽  
Image Features ◽  
State Recognition ◽  
Quantitative Metrics ◽  
Proposed Model ◽  
Essential Region

The human visual system (HVS) seeks toward select relevant region in the direction of level rear method attempts. visual concentration effort to guess the essential region of films or imagery observed through an individual eye. Such representations, are functioned to areas similar to workstation work, MPEG conventions, and an eminence evaluation. while numerous models are expected, only some of them be pertinent enroute for high dynamic range (HDR) picture substance, in addition to no effort has been completed for HDR visualization. Furthermore, the disadvantage inside the obtainable form is with the intention, they couldn't reproduce the uniqueness of HVS beneath the extensive shining array established in HDR substance. This paper gets the better of these troubles by the process approach to represent the bottom-up visual saliency for HDR input through merge spatial and temporal image features. An examine of a human eye ball movement information make sure the efficiency of the proposed model. Evaluation using 3 well-known quantitative metrics show that the proposed model significantly gets better predictions of visual concentration for HDR substance.

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