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    • 4. 发明专利
    • A multi-level encryption scheme for H.265/HEVC based on syntax elements scrambling
    • AU2020100421A4
    • 2020-04-30
    • AU2020100421
    • 2020-03-19
    • FANG YUMINGTU RONGXINWEN WENYING DRYANG YONGZHANG YUSHU
    • WEN WENYINGTU RONGXINFANG YUMINGZHANG YUSHUYANG YONG
    • H04N19/61H04N19/18
    • Abstract: High Efficiency Video Coding (HEVC) encryption can be encrypted by syntax elements. To our best known, almost all of current scheme of HEVC encryption encrypt the whole video in order to obtain unviewable information. However, it cannot meet the needs of all customers. In many cases, users would like visible information in encrypted video to satisfy their requirements. Aiming at this demand, we propose a multi-level encryption scheme in which each level can obtain different amount of information. First, we use AES-CTR to generate a pseudo-random number sequence. Then, the main syntax elements in H.265 /HEVC encoding process are encrypted by a pseudo-random sequence. In the process, only one syntax element is encrypted at a time. We find that the encryption of the luma and chroma intra prediction model (IPM) and the scrambling of DCT coefficient sign can achieve multi-level encryption of visual information. The experimental results meet our expectations. Meanwhile, users can flexibly choose the encryption level according to their various requirements. (a)b c) (d) e (i hp (0) (k) ()(q) i r) tsp (t) Fig.1 Proposed encryption approach applied to steam Akiyo and Bowing, demonstrating different amount of visual information in three levels. The first column: the original frames; the second column: encrypted frames with lightweight level encryption; the third column: encrypted frames with Medium level encryption;the fourth column: encrypted frames with heavyweight level encryption; the fifth column: decrypted frames of each levels.
    • 6. 发明专利
    • Single image deraining algorithm based on multi-scale dictionary
    • AU2020100460A4
    • 2020-04-30
    • AU2020100460
    • 2020-03-26
    • HUANG SHUYING DRXU YATING MISSYANG YONG PROF
    • HUANG SHUYINGXU YATINGYANG YONG
    • G06T5/00G06N20/00
    • We aim to remove the rain tracks from the rain images and retain the structure information of the original rain map to the greatest extent. Due to the complexity of the rain layer, the rainless background layer cannot be directly obtained at one time. Therefore, We according to the rain streaks of many aspects, such as sparsity, structural and directional information, proposed a new single image to the rain, which framework of the method through constant iterative update background layer, the sparse coefficient of the rain layer, the rain dictionary and a new rain layer, thereby gaining a free-rain image. Our main contribution can be divided into three parts: (I) A very effective convolutional sparse coding framework is proposed to iteratively update the rain layer and the background layer. (II) Considering the multi-scale characteristics of the noise rain layer information in the rain image taken in reality under different the depth of field, we proposed the method of learning multi dictionary, and carried out the convolution sparse coding for the raindrop information of different sizes (III) In the process of solving the rain layer, we proposed to use the multi-scale dictionary to solve the updated rain layer information, and to use the consistency of rain direction and the structure of raindrops to propose two prior constraints based on gradient, so as to obtain better results. Finally, ADMM algorithm is used to solve the model alternately to obtain the rainless image with rich details.