Graphic-processing-unit-accelerated real-time exposure fusion method using pixel-level optimal exposure criterion
Jun Zhang, Shiqiang Hu · Optical Engineering · 2012
High dynamic range (HDR) imaging is an important and challenging research topic in computational photography. A simple but effective image fusion method is proposed to accomplish the multi-exposure image composition in both static and dynamic scenes. The foundation of the proposed method is an experiential criterion that optimizes the exposure that occurs at a dramatic alteration point in the low dynamic range image sequence (LDRI). To extract these well-exposed pixel vectors, each pixel curve formed by the pixel vectors at same position along all frames in the LDRIs is first preprocessed by the chord length parameterization. Then a single high-quality pseudo-HDR image can be extracted directly and efficiently from the LDRIs using a pixel-level fusion index matrix derived from the first- and second-order difference quotients of the preprocessed pixel curves. The main advantage of the proposed method is its use of a single independent pixel in computing. It is highly parallel, allowing a graphic processing unit-based, real-time implementation. The experiments on various scenes discussed here indicate that the proposed exposure fusion method can combine a large image sequence with 10 megapixels into a visually compelling pseudo-HDR image at a rate of 30 frames/s on a consumer hardware.