Tone mapping

About: Tone mapping is a research topic. Over the lifetime, 1713 publications have been published within this topic receiving 48490 citations.

Quality Measurement for High Dynamic Range Omnidirectional Image Systems

Abstract: From the perspective of optimizing the visual experience of the omnidirectional system, this article explores the terminal image quality of the high dynamic range omnidirectional image (HOI) system for the first time. The HOI system has higher contrast and wider field of view perception, but its complex imaging process poses a challenge to quality measurement. In this article, we propose a novel quality measurement method for HOI (QM-HOI) system based on distortion perception and brain information-processing mechanism. Because HOI system may encounter single distortion or mixed distortion, the proposed method consists of two modules, i.e., local progressive distortion model (LPDM) and global mixed distortion model (GMDM). LPDM is designed to mainly extract local features based on the different perception effects that tone mapping (TM) operators impart to coding distortion in different luminance regions. GMDM is designed to jointly consider the structure distortion caused by coding and the color distortion of TM. The extracted features are formed into feature vectors to predict the visual quality of the distorted HOIs. A new HOI subjective evaluation dataset with multidistortion is established, called NBU-HOID, specialized for the design and testing of the proposed method. Experimental results show that the objective measurement results of the proposed method is better than the state-of-the-art methods, and more in line with the human perception. We will also provide the NBU-HOID dataset free of charge shortly afterward.

Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor.

Abstract: The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time.

Image processing method and device, storage medium, and electronic equipment

Abstract: The embodiment of the invention discloses an image processing method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining multiple frames of raw imagesand a first synthetic image; identifying a face region and a target overexposure region in the first composite image; obtaining brightness relations between the target overexposure area and the face area in the multiple frames of raw images; determining the expected brightness of the target overexposure area according to the brightness relations, wherein the expected brightness comprises the expected brightness of each pixel point in the target overexposure area; generating a first tone mapping operator corresponding to the target overexposure area according to the current brightness of the target overexposure area in the first composite image and the expected brightness; according to the preset tone mapping operator and the first tone mapping operator, carrying out tone mapping processingon the first composite image to generate a second composite image. The phenomenon that the brightness difference between the target overexposure area and the human face in the HDR image is obvious iseliminated.

Improved tone mapping operator for HDR coding optimizing the distortion/spatial complexity trade-off.

Abstract: A common paradigm to code high dynamic range (HDR) im-age/video content is based on tone-mapping HDR pictures to low dynamic range (LDR), in order to obtain backward compatibility and use existing coding tools, and then use inverse tone mapping at the decoder to predict the original HDR signal. Clearly, the choice of a proper tone mapping is essential in order to achieve good coding performance. The state-of-the-art to design the optimal tone mapping operator (TMO) minimizes the mean-square-error distortion between the original and the predicted HDR image. In this paper, we argue that this is suboptimal in rate-distortion sense, and we propose a more effective TMO design strategy that takes into account also the spatial complexity (which is a proxy for the bitrate) of the coded LDR image. Our results show that the proposed optimization approach enables to obtain substantial coding gain with respect to the minimum-MSE TMO.

Structure revealing of low-light images using wavelet transform based on fractional-order denoising and multiscale decomposition

Abstract: Images captured in low-light environment often lower its quality due to low illumination and high noise. Hence, the low visibility of images notably degrades the overall performance of multimedia and vision systems that are typically designed for high-quality inputs. To resolve this problem, numerous algorithms have been proposed in extant literature to improve the visual quality of low-light images. However, existing approaches are not good at improving overexposed portions and produce unnecessary distortion, which leads to poor visibility in images. Therefore, in this paper, a new model is proposed to prevent overenhancement, handle uneven illumination, and suppress noise in underexposed images. Firstly, the input image is converted into HSV color space. Then, the obtained V component is decomposed into high- and low-frequency subbands using the dual-tree complex wavelet transform. Secondly, a denoised model based on fractional-order anisotropic diffusion is applied on high-pass subbands. Thirdly, multiscale decomposition is used to extract more details from low-pass subbands, and inverse transformation is performed to compute final V. Next, sigmoid function and tone mapping are used on V-channel to prevent data loss and achieve robust results. Finally, the image is reconstructed and converted to RGB color space to achieve enhanced performance. Comparative experimental statistics show that the proposed method achieves high efficacy and outperforms the traditional approaches in terms of overall performance.