Tone mapping

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

Depth-Stretch: Enhancing Depth Perception Without Depth

Abstract: A simple and efficient method is presented to enhance the depth perception of an image. The approach termed Depth-Stretch (D-stretch) is a tone mapping operation that is applied to the shading component of the given image. Although re-rendering a scene under geometric transformations typically requires extracting the 3D model of the scene, we show that under very simple assumptions D-stretch can be implemented without 3D reconstruction, while still providing a convincing effect of depth enhancement.

HDR-NeRF: High Dynamic Range Neural Radiance Fields.

Abstract: We present High Dynamic Range Neural Radiance Fields (HDR-NeRF) to recover an HDR radiance field from a set of low dynamic range (LDR) views with different exposures. Using the HDR-NeRF, we are able to generate both novel HDR views and novel LDR views under different exposures. The key to our method is to model the physical imaging process, which dictates that the radiance of a scene point transforms to a pixel value in the LDR image with two implicit functions: a radiance field and a tone mapper. The radiance field encodes the scene radiance (values vary from 0 to +infty), which outputs the density and radiance of a ray by giving corresponding ray origin and ray direction. The tone mapper models the mapping process that a ray hitting on the camera sensor becomes a pixel value. The color of the ray is predicted by feeding the radiance and the corresponding exposure time into the tone mapper. We use the classic volume rendering technique to project the output radiance, colors, and densities into HDR and LDR images, while only the input LDR images are used as the supervision. We collect a new forward-facing HDR dataset to evaluate the proposed method. Experimental results on synthetic and real-world scenes validate that our method can not only accurately control the exposures of synthesized views but also render views with a high dynamic range.

Laser display color adjusting method and device thereof

Abstract: The invention discloses a laser display color adjusting method, which comprises steps: raw data signals in a RGB format of one frame of laser image are acquired; the format of the raw data signals is converted to generate data signals in an L*C*h format; a tone corresponding to a tone range with concentrated pixel points is recorded to be a main tone of the laser image and a main tone influence function is set; a saturation influence function is set, the main tone influence function is introduced at the same time if the main tone exists in the laser image, and saturation mapping is carried out on all pixel points in the data signals; a tone weight function is set to carry out tone mapping on all pixel points in the data signals; a light illumination mapping function is set to carry out light illumination mapping on all pixel points; and the format of the data signals is converted to the RGB format and display is carried out. By adopting different tone, saturation and light illumination mapping relationships, ill questions of over saturation, over illumination, easy visual fatigue and the like can be solved. The invention also discloses a laser display color adjusting device.

Spectral information and spatial color computation

Abstract: In real world no color exists. Only spectral light distributions interact to form the final color sensation. This paper presents preliminary experiments whose purpose is to test the robustness of a spatial color computation in relation to changes in the acquisition of spectral information. The basic idea is that human vision system has evolved into a robust system to acquire visual information, in this case the color, adapting to varying illumination conditions to guarantee color constancy. The presented experiments test changes in the output of a Retinex-derived tone mapping operator, varying illuminants and color matching function curves. Synthetic high dynamic range multispectral images have been computed by a photometric ray tracer using different illuminants. Then, using standard and modified color matching functions, a set of high dynamic range RGB images has been created. This set has been converted to standard RGB images using a linear tone mapping algorithm with no spatial color computation and one based on Retinex, performing a spatial color normalization. A discussion of the results is presented.

A non-uniform quantization scheme for visualization of CT images.

Abstract: Medical science heavily depends on image acquisition and post-processing for accurate diagnosis and treatment planning. The introduction of noise degrades the visual quality of the medical images during the capturing process, which may result in false perception. Therefore, medical image enhancement is an essential topic of research for the improvement of image quality. In this paper, a clustering-based contrast enhancement technique is presented for computed tomography (CT) images. Our approach uses the recursive splitting of data into clusters targeting the maximum error reduction in each cluster. This leads to grouping similar pixels in every cluster, maximizing inter-cluster and minimizing intra-cluster similarities. A suitable number of clusters can be chosen to represent high precision data with the desired bit-depth. We use 256 clusters to convert 16-bit CT scans to 8-bit images suitable for visualization on standard low dynamic range displays. We compare our method with several existing contrast enhancement algorithms and show that the proposed technique provides better results in terms of execution efficiency and quality of enhanced images.