Single image detail enhancement via residual homogeneity
In this paper, we put forward a novel method in single image detail enhancement — residual homogeneity (RH). Residual homogeneity is a statistic result when we test different kinds of blocks in database, finding that blocks in residual images are with similar structure, that is, they are homogenous. Based on residual homogeneity, we make a simple assumption that detail layer of a single image is residual component after fast in-place search and block match. Then images are enhanced by applying framework of RH. Unlike many popular algorithms that need to adjust parameters by manual operation to get best performance, our approach is adaptive. Besides, many algorithms output images with intensity change, our RH can keep images from over enhancement with a nature look. RH is also robust to low bit rate H.265 system and runs faster than most popular methods. Moreover, it can be easily FPGA implemented as well. Numbers of experiments testify that our algorithm is robust with good performance both subjectively and objectively.