Novatek Microelectronics Corp.

Xin Huang

Fan-Di Jou

Xi Tian

Pengyuan Hu

Ting Peng

Chun Wang

Chun-Wei Chen

JianHua Liang

YuanJia Du

Yongchao Li

Yu Bai

Cong Zhang

Kai Kang

Fan Wang

Jingzhi Zhang

A method and an image processing device for generating an image filter are proposed. The method includes the following steps. A first image is received and inputted into a pre-trained convolutional neural network (CNN) model, and the image filter corresponding to the first image is obtained based on an output result of the pre-trained CNN model.

Method and image processing device for generating image filter

A video encoder, a video decoder and a video system are provided. The video encoder performs a video encoding operation on a first video frame stream to generate an encoded stream to the video decoder, wherein the encoded stream contains deblocking filtering information. The video decoder performs a video decoding operation on the encoded stream to generate a second video frame stream. The video decoder determines whether to forcibly perform a deblocking filtering operation on a current block of a current frame of the second video frame stream according to the deblocking filtering information.

Video encoder, video decoder, and video system

A video processing method includes: an i-th block of a target frame partitioned into a plurality of blocks is received; at least one of a spatial attribute parameter and a temporal attribute parameter of an i-th block of the target frame is determined; and at least one of a delta quantization parameter and a modified Lagrange multiplier is determined according to at least one of the spatial attribute parameter and the temporal attribute parameter, for encoding the i-th block of the target frame.

Video processing method

The disclosure provides a method and an image processing device for video bit-rate control. The method includes the following steps. A designated distortion value and a maximum bit-rate value are received. A Lagrange multiplier and a quantization parameter (QP) of a current frame among a sequence of video frames are estimated according to the designated distortion value and the maximum bit-rate value. The current frame is encoded according to the estimated Lagrange multiplier and the estimated QP.

Method and image processing device for video bit-rate control

A video encoding apparatus and a video encoding method are provided. The video encoding apparatus includes an integer-pel motion estimation (IME) circuit, a temporal noise reduction (TNR) circuit, a fractional-pel motion estimation (FME) circuit and an encoding circuit. The IME circuit provides the first motion vector, the error value and the co-located error value of the current block in the current frame to the TNR circuit. By using the first motion vector, the error value and the co-located error value of the current block in the current frame, the TNR circuit performs the temporal filtering process on the current block in an original image data to produce a denoised image data to the FME circuit.

Video encoding apparatus and video encoding method that perform filtering operation during video encoding process

An image processing method and an image processing apparatus that utilize scrolling text information and moving edge-pairs of an edge map to determine text regions in interpolated frame is introduced herein. Text blocks are detected according to the moving edges-pair of the edge map. Next, a first moving vector histogram and a second moving vector histogram are built according to the detected text blocks. An existence of scrolling text and motion vector of the scrolling text in the frames are determined according to the first and second moving vector histograms. A scrolling text region in at least one of the first frame and the second frame is determined in block line unit, and positions of each scrolling text pixels in an interpolated are determined according to the motion vector of the scrolling text and the scrolling text region in the at least one of the first frame and the second frame.

Method for scrolling text processing and image processing apparatus using the same

A motion estimation method for a frame rate converter includes generating a plurality of unidirectional motion vectors (MVs) based on a first original frame and a second original frame; classifying each of the plurality of unidirectional MVs as a reliable MV or a mismatch MV; mapping the reliable MV onto one of a plurality of blocks of an interpolation frame; classifying each of the plurality of blocks as a high confidence block or a low confidence block based on whether there is at least one reliable MV mapped onto the block; and determining an assigned MV for each of the high confidence block by selecting one of the at least one reliable MV mapped onto the high confidence block.

Motion estimation method for frame rate converter and video processor using the same

The disclosure is directed to a video processing apparatus and a video processing method thereof. In one of the exemplary embodiments, the disclosure is directed to a video processing apparatus which includes not limited to a storage medium configured to store a first video file, a down-scaling module coupled to the storage medium and configured to down-scale the first video file into a second video file, a learning machine module configured to receive the first video file and a third video file which is processed from the second multimedia file and generate a trained model out of the first video file and the third video file, and a transmitter configured to transmit a data package which comprises a compression of the second video file and a compression of the trained model.

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Xi'an, China

Xin Huang