Improving Compression Performance in Bit Depth SVC with a Prediction Filter

High dynamic range (HDR) is a technique that allows a great dynamic range of luminance between the lightest and darkest area of an image. For video compression, the HDR sequence is reconstructed by inverse tone-mapping a compressed low dynamic range (LDR) version of the original HDR content. In this paper, we show that the appropriate choice of a Tonemapping operator (TMO) can significantly improve the reconstructed HDR quality. It is used to compress a large range of pixel luminance in to smaller range that is suitable for display on devices with limited dynamic range. we formulate a numerical optimization problem to find the tone-curve that minimizes the expected mean square error (MSE) in the reconstructed HDR sequence. We also develop a simplified model that reduces the computational complexity of the optimization problem to a closed-form solution. It is also shown that the LDR image quality resulting from the proposed methods matches that produced by perceptually-based TMOs