Image set modeling by exploiting temporal-spatial correlations and photo album compression

With the advance of digital photographing technology, large amount of personal photos are created and stored online or in personal computers. To save storage space and transmission bandwidth, we proposed a new photo album compression scheme by using both intra prediction and inter prediction to reduce spatial and temporal redundancy. Specifically, we first cluster the images so that each cluster containing a set of similar images is a group of pictures (GOP) with variable length. A graph framework is proposed then, in which an optimal “IPPP...P” GOP structure is derived from every cluster by finding the minimum spanning tree (MST) at a minimum prediction cost. Finally, the photo album is compressed as a whole like a video sequence, by High Efficiency Video Coding (HEVC), according to the predictive order of the optimal structures. The experimental results show that our scheme achieves around 60% improvement over only using JPEG compression.