Abstract

One of the significant qualities of the human vision, which differentiates it from computer vision, is so called attentional control, which is the innate ability of our human eyes to select what visual stimuli to pay attention to at any moment in time. In this sense, the visual salience detection model, which is designed to simulate how the human visual system (HVS) perceives objects and scenes, is widely used for performing multiple vision tasks. This model is also in high demand in the tone mapping technology of high dynamic range images (HDRIs). Another distinct quality of the HVS is that our eyes blink and adjust brightness when objects are in their sight. Likewise, HDR imaging is a technology applied to a camera that takes pictures of an object several times by repeatedly opening and closing a camera iris, which is referred to as multiple exposures. In this way, the computer vision is able to control brightness and depict a range of light intensities. HDRIs are the product of HDR imaging. This article proposes a novel tone mapping method using CCH-based saliency-aware weighting and edge-aware weighting methods to efficiently detect image salience information in the given HDRIs. The two weighting methods combine with a guided filter to generate a modified guided image filter (MGIF). The function of the MGIF is to split an image into the base layer and the detail layer which are the two elements of an image: illumination and reflection, respectively. The base layer is used to obtain global tone mapping and compress the dynamic range of HDRI while preserving the sharp edges of an object in the HDRI. This has a remarkable effect of reducing halos in the resulting HDRIs. The proposed approach in this article also has several distinct advantages of discriminative operation, tolerance to image size variation, and minimized parameter tuning. According to the experimental results, the proposed method has made progress compared to its existing counterparts when it comes to subjective and quantitative qualities, and color reproduction.

Highlights

  • A camera is designed to perform an human visual system (HVS)-like task—to capture the surroundings and provide information for higher-level processing

  • This paper proposes a novel approach to tone mapping of high dynamic range images (HDRIs), which has two parts: the chromatics-based tone mapping operators (TMOs) and the chromatic adaptive transform (CAT)

  • The experiments apply several publicly available HDRIs widely used in assessing tone mapping performance and the images captured under five standard illuminations (D, SWF, TL84, A, and UV)

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Summary

Introduction

A camera is designed to perform an HVS-like task—to capture the surroundings and provide information for higher-level processing. Given this similarity, a naïve conception would be that a physical scene captured by a camera and viewed on a display device should invoke the exact same. Sci. 2019, 9, 4658 response as observing the scene directly. This is very seldom the case, for a number of reasons. The camera and the display devices are unable to cover wider ranges of luminance which the HVS can detect simultaneously, and this implies that there is more visual information available in the real-life scene than what can be captured and reproduced

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