One Novel Rate Control Scheme for Region of Interest Coding

Chen, Xi; Wu, Zongze; Xie, Zhengchao; Xiang, Youjun; Xie, Shengli

doi:10.1007/978-3-319-42297-8_14

Cited by 5 publications

(4 citation statements)

References 3 publications

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“…First, the maximum compression or maximum sampling rate value (S max ) must be defined. Given an image width (image width ) and the number of blocks N block in which the image is going to be divided at the larger side (width or height), the block side length (l) is computed see Equation (5). The maximum sampling rate Equation (6) is related to the original image size and the number of blocks in which it was divided.…”

Section: Translation Of Pr Into a Sample Ratementioning

confidence: 99%

“…In contrast to downsampling algorithms, which equally decrease the quality of the whole original image, adaptive downsampling algorithms aim to assign higher sampling rates to complex or detailed areas [4]. There are several known methods to assign an adaptive sampling rate to the different blocks of an image based on frequency analysis [5] or space (luminance) analysis [6]. This set of sampling rates constitutes the sampling rate vector.…”

Section: Introductionmentioning

confidence: 99%

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Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality

et al. 2021

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This paper presents a new adaptive downsampling technique called elastic downsampling, which enables high compression rates while preserving the image quality. Adaptive downsampling techniques are based on the idea that image tiles can use different sampling rates depending on the amount of information conveyed by each block. However, current approaches suffer from blocking effects and artifacts that hinder the user experience. To bridge this gap, elastic downsampling relies on a Perceptual Relevance analysis that assigns sampling rates to the corners of blocks. The novel metric used for this analysis is based on the luminance fluctuations of an image region. This allows a gradual transition of the sampling rate within tiles, both horizontally and vertically. As a result, the block artifacts are removed and fine details are preserved. Experimental results (using the Kodak and USC Miscelanea image datasets) show a PSNR improvement of up to 15 dB and a superior SSIM (Structural Similarity) when compared with other techniques. More importantly, the algorithms involved are computationally cheap, so it is feasible to implement them in low-cost devices. The proposed technique has been successfully implemented using graphics processors (GPU) and low-power embedded systems (Raspberry Pi) as target platforms.

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Section: Translation Of Pr Into a Sample Ratementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality

et al. 2021

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“…The work of [11] and [12] deal with improving the rate control algorithm of the encoder. Chen et al [11] use a weighting coefficient to define the significance of the ROI with respect to the background, and then use it to calculate the Mean Absolute Difference (MAD) of the ROI and the background. The authors did not provide any specific method to define the weighing parameter.…”

Section: Literature Reviewmentioning

confidence: 99%

Compression of Patient’s Video for Transmission Over Low Bandwidth Network

et al. 2019

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In this paper, we propose a solution for video transmission over a low-bandwidth network that enables a physician to take in charge of remote trauma patient. We propose and analyze a method based on an H.264 compression scheme that relies on transmitting high-quality video of a moving and dynamic region of interest while scarifying quality in the background. Our method is motivated by the problem of limited bandwidth usually encountered in air-to-ground communication channels. We propose to use a region of interest with smoothed edges to increase the video quality of the transition between the regions of various qualities. The moving region of interest, covering the torso and the head, is segmented and tracked by using the skeleton information provided by a Kinect camera. Our proposed compression scheme respects the realtime, low-complexity, and interoperability constraints. We have analyzed the results of our method obtained with various bit rate targets and have shown that a visual assessment of a patient is achievable over very low bandwidth. INDEX TERMS Video compression, telemedicine, region of interest, body skeleton, H.264, emergency medical services.

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“…The motion information of the ROIs is estimated by macroblock padding and polygon matching. In [5], authors propose a novel rate control scheme for ROI coding. They set the area covering people are interested in as the ROI to preserve better quality than the background.…”

Section: A the Concept Of Regions Of Interest Applied In Image / Vidmentioning

confidence: 99%

Human Visual System-based Unequal Error Protection for Robust Video Coding

Serrar¹,

Abra²,

Youssfi³

2017

ijacsa

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Abstract-To increase the overall visual quality of the video services without increasing data rate, a human visual systembased video coding, founded on a hierarchy of the video stream in different levels of importance, is developed. Determining these importance levels takes in count three classification criteria: the position of current image in the group of images (image level), the importance of the motion vectors of macroblocks in the current image (macroblock level) and belonging or not of a pixel in a spatial region of interest (pixel level). At the end of this classification process, an interpolation between the results of the three-level selection allows to establish an index of importance for each macroblock of the image to be encoded. This index determines the type of channel coding to be applied to the corresponding macroblock. Tests have shown that the technique presented in this paper achieves better results in PSNR and SSIM (structural similarity) than an equal error protection technique.

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One Novel Rate Control Scheme for Region of Interest Coding

Cited by 5 publications

References 3 publications

Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality

Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality

Compression of Patient’s Video for Transmission Over Low Bandwidth Network

Human Visual System-based Unequal Error Protection for Robust Video Coding

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