Digital photo similarity analysis in frequency domain and photo album compression

With the increasing popularity of digital camera, organizing and managing the large collection of digital photos effectively are therefore required. In this paper, we study the techniques of photo album sorting, clustering and compression in DCT frequency domain without having to decompress JPEG photos into spatial domain firstly. We utilize the first several non-zero DCT coefficients to build our feature set and calculate the energy histograms in frequency domain directly. We then calculate the similarity distances of every two photos, and perform photo album sorting and adaptive clustering algorithms to group the most similar photos together. We further compress those clustered photos by a MPEG-like algorithm with variable IBP frames and adaptive search windows. Our methods provide a compact and reasonable format for people to store and transmit their large number of digital photos. Experiments prove that our algorithm is efficient and effective for digital photo processing.