Korea Advanced Institute of Science and Technology

Silicon Works Co., Ltd.

Agency for Defense Development

Dae Eun Kim

Mun Churl Kim

Dong Hyun Kim

Yong Woo Kim

Seung Ho Baek

Jong Hwan Ko

Soo Ye Kim

Woo Suk Ha

Jeung Won Choi

Se Hwan Ki

Sang Yeon Kim

No Hyeok Park

Ki Nam Jun

Ju Hyun Jung

In this invention, we propose a convolutional neural network (CNN) based architecture designed for the ITM to HDR consumer displays, called ITM-CNN, and its training strategy for enhancing the performance based on image decomposition using the guided filter. We demonstrate the benefits of decomposing the image by experimenting with various architectures and also compare the performance for different training strategies. To the best of our knowledge, this invention first presents the ITM problem using CNNs for HDR consumer displays, where the network is trained to restore lost details and local contrast. Our ITM-CNN can readily up-convert LDR images for direct viewing on an HDR consumer medium, and is a very powerful means to solve the lack of HDR video contents with legacy LDR videos.

Method and apparatus for inverse tone mapping

Provided are a method and an apparatus for performing scalable video decoding, wherein the method and the apparatus down-sample input video, determine the down-sampled input video as base layer video, generate prediction video for enhancement layer video by applying an up-scaling filter to the base layer video, and code the base layer video and the prediction video, wherein the up-scaling filter is a convolution filter of a deep neural network.

Apparatus and method for performing scalable video decoding

The present invention provides a technology that separates a low-contrast-ratio image into sublayer images, classifies each sublayer image into several categories in accordance with the characteristics of each sublayer image, and learns a transformation matrix representing a relationship between the low-contrast-ratio image and a high-contrast-ratio image for each category. In addition, the present invention provides a technology that separates an input low-contrast-ratio image into sublayer images, selects a category corresponding to each sublayer image, and applies a learned transformation matrix to generate a high.

Inverse tone mapping method

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Daejeon, South Korea

Dae Eun Kim