Saliency guided wavelet compression for low-bitrate image and video coding

We propose an improved saliency guided wavelet compression scheme for low-bitrate image/video coding applications. Important regions (faces in security camera feeds, vehicles in traffic surveillance) get degraded significantly at low bitrates by existing compression standards, such as JPEG/JPEG-2000/MPEG-4, since these do not explicitly utilize any knowledge of which regions are salient. We design a compression algorithm which, given an image/video and a saliency value for each pixel, computes a corresponding saliency value in the wavelet transform domain. Our algorithm ensures wavelet coefficients representing salient regions have a high saliency value. The coefficients are transmitted in decreasing order of their saliency. This allows important regions in the image/video to have high fidelity even at very low bitrates. Further, our compression scheme can handle several salient regions with different relative importance. We compare the performance of our method with the JPEG/JPEG-2000 image standards and the MPEG-4 video standard through two experiments: face detection and vehicle tracking. We show improved detection rates and quality of reconstructed images/videos using our Saliency Based Compression (SBC) algorithm.