Abstract
ABSTRACT In this paper, we present BoostHDR, a novel method for compressing high dynamic range (HDR) images. Thealgorithm leverages on a novel segmentation-based tone mapping operator (TMO) which relaxes the no seamsconstraint. Our method can work with both JPEG and JPEG2000 encoders. Moreover, it provides better resultscompared to the state of the art in HDR images compression algorithms in terms of bit per pixels (bpp), andvisual quality using objective metrics.Keywords: HDR Imaging, HDR Image Compression 1. INTRODUCTION The HDR content capturing is now becoming very popular, allowing consumers to capture HDR images withcompact and DLSR cameras or even mobile phones. Moreover, DSLRs can be used for capturing HDR videos, 12 and HDR video cameras are starting to emerge. 6,20,27 This new era in capturing allows users to represent thefull luminance range that the human visual system (HVS) can perceive.On the other hand, HDR content requires more memory for storing the extra dynamic range information thanconventional imaging at 8-bit or low dynamic range (LDR) imaging. For example, an uncompressed HDR pixel,represented using 32-bit oating point, can require four times the amount of memory of an uncompressed LDRpixel at 8-bit. This can negatively a ect performances too, because more bandwidth is needed. For instance, itwould be prohibitive to manage a photographic gallery of uncompressed HDR images or to play HDR videos.In recent years, algorithms for HDR content memory compression have been proposed. These methods aretypically based on existing compression standards such as JPEG, JPEG2000, and MPEG, which can be modi edor extended to handle HDR information. However, the community has not agreed on a common standardencoding yet. This is quite critical, because the HDR imaging has reached the market as extra feature or appfor cameras and mobile phones.In this paper, we present a novel compression algorithm which is based on an segmentation-based TMO, andexisting image compression standards such as JPEG and JPEG2000. Our key contributions are: Backward compatibility : the information in compressed images can be visualized by a JPEG or JPEG2000standard viewer. This allows users to visualize part of the content when software that can decode ourcompression algorithm is not present. Improvement over state of the art : our proposed solution provides better performances in terms of visualquality and bpp than JPEG-HDR compression by Ward and Simmmons,
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