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It is difficult to apply existing exposure methods to a resource-constrained platform. Their pyramidal image processing and quality measures for interesting areas that need to be preserved require a lot of time and memory. The work presented in this paper is a DCT-based HDR exposure fusion using multiexposed image sensors. In particular, it uses the quantization process in JPEG encoding as a measurement of image quality such that the fusion process can be included in the DCT-based compression baseline. To enhance global image luminance, a Gauss error function based on camera characteristics is presented. In the simulation, the proposed method yields good quality images, which balance naturalness and object identification. This method also requires less time and memory. This qualifies our technique for use in resource-constrained platforms.

Abstract. An image toning method for low dynamic range image compression is presented. The proposed method inserts tone mapping into JPEG baseline instead of postprocessing. First, an image is decomposed into detail, base, and surrounding components in terms of the discrete cosine transform coefficients. Subsequently, a luminance-adaptive tone mapping based on the human visual sensitivity properties is applied. In addition, compensation modules are added to enhance the visually sensitive factors, such as saturation, sharpness, and gamma. A comparative study confirms that the transmitted compression images have good image quality. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Many tone‐mapping methods have developed efficient tone compression and local contrast enhancement techniques for high dynamic‐range imaging. Local tone mapping enhances the image quality to reveal the details; however, it causes artefacts such as halos. Halo artefacts appear around the edges of an image and lead to deterioration in the overall image quality. Detail‐base separation and multi‐scale methods have been developed to reduce halo artefacts. Detail‐base separation methods divide the image into a detail layer and base layer using an edge‐preserving filter and process each layer independently. Multi‐scale methods alleviate artefacts such as halos, noise, and awkward global toning using a weighted sum of single‐scale images. These methods have several inherent problems including the complexity of the edge‐preserving filter and multi‐processing redundancy. Therefore, in this study, a novel surround map is presented to resolve halo artefacts and enhance local details in single‐scale processing.