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As digital cameras become more and more popular recently, it is very easy for us to take many digital photos. Unfortunately, they are rarely true measurements of relative radiance in the scene due to the limited dynamic range in the image acquisition devices. High dynamic range (HDR) images emphasis in image processing fields because they can accommodate a greater dynamic range of luminance between the brightest and darkest parts of an image. Dynamic range is the ratio between the brightest and darkest luminance values of a scene. In general, human eyes can handle a very large dynamic range of approximately 1:1 in a single view. However, a standard photo taken with a standard camera with film or an electronic imaging array always has a limited dynamic range [1]. A standard image, called a LDR image, cannot reproduce the luminance ratio observed in the real world. A scene containing very bright highlights and deep shadows always loses some detail if the exposure time is not suitably determined. Over the past decade, many researchers have developed HDR imaging techniques (Debevec & Malik, 1997)(Reinhard et al, 2005) (Reinhard et al, 2007). Debevec and Malik proposed a method to recover the single high dynamic range radiance map from multiple images with different exposure times (Debevec & Malik, 1997), this method has been implemented in many HDR software.

Robust Watermarking Framework for High Dynamic Range Images Against Tone-Mapping Attacks