METHOD AND APPARATUS FOR ENCODING/DECODING IMAGE USING DEEP NEURAL NETWORK BASED BLUR IMAGE LEARNING

摘要

Disclosed are a method and an apparatus which can increase compression efficiency by encoding a still image and/or a moving image after performing blur-preprocessing for each block included in the image based on a learning result using a deep neural network, instead of directly encoding the image, and restoring blur images at the time of decoding. An image encoding method according to an embodiment of the present disclosure includes the following steps: dividing an image to be encoded into one or more unit areas; deriving a restoration parameter or blur level for each of the unit areas; performing blurring for each of the unit areas to obtain blur images; and encoding the blurred image. The step of deriving a restoration parameter or blur level for each of the unit areas may be performed by using a model generated through a process of determining one or more sample images and restoration parameters for each of the blurred images of the sample images. The blur level for the unit area may be determined based on the complexity of the unit area.;COPYRIGHT KIPO 2018