Spatio-temporal Tone Mapping Operator Based on a Retina Model

Abstract

From moonlight to bright sun shine, real world visual scenes contain a very wide range of luminance; they are said to be High Dynamic Range (HDR). Our visual system is well adapted to explore and analyze such a variable visual content. It is now possible to acquire such HDR contents with digital cameras; however it is not possible to render them all on standard displays, which have only Low Dynamic Range (LDR) capabilities. This rendering usually generates bad exposure or loss of information. It is necessary to develop locally adaptive Tone Mapping Operators (TMO) to compress a HDR content to a LDR one and keep as much information as possible. The human retina is known to perform such a task to overcome the limited range of values which can be coded by neurons. The purpose of this paper is to present a TMO inspired from the retina properties. The presented biological model allows reliable dynamic range compression with natural color constancy properties. Moreover, its non-separable spatio-temporal filter enhances HDR video content processing with an added temporal constancy.

Evaluation of HDR video tone mapping for mobile devices

“…In addition TMOs for HDR video need to also take into account temporal coherency [3], [6] , [8]. This because significant luminance changes may occur in a sequence of frames and, if the frames are processed individually, this may cause some noticeable flickering as the individual processing of a single frame has not taken into consideration the luminance levels of the adjacent frames or of the overall video.…”

“…The spatio-temporal TMO proposed in [3] is based on a model of the retina local adaptation properties developed by Meylan et al [28] and is complemented by spatio-temporal filters of the retina. This work simulates some of the foveal retina functionalities and includes temporal coherency and thus is able to avoid flicker.…”

“…In this paper we present the results of the evaluation of six HDR video TMOs that focus on different properties. The TMOs evaluated were: Spatio-Temporal based on a Retina model [3], the model of visual adaptation [4], the method proposed by [5] that encodes HDR video using a model of human cones, the display adaptive technique [6], a time-dependent visual adaptation approach [7], and the TMO proposed by Boitard et al [8] that takes account temporal coherency. This evaluation intends to determine:…”

A real-time system for capturing HDR videos

“…Only few operators specific to HDR video content have been proposed. Benoit et al [2] propose a model based on properties of the human retina. HDR video is enhanced by a non-separable spatio-temporal filter with added temporal constancy.…”

Live HDR video streaming on commodity hardware

“…The majority of these have been for static images, but more recently a number of TMOs for HDR video have been proposed which take into account potential temporal artefacts. 5,6 When it comes to displays, most are currently LDR, although a commercial HDR display, the SIM2 HDR47ES6MB, capable of displaying a peak luminance of 6,000 cd/m 2 is available. 7 Where the dynamic range of the display matches that of the delivered lighting, the images can be displayed in a straightforward manner.…”