Industrial Applications of Ultrahigh Definition Video Coding With an Optimized Supersample Adaptive Offset Framework

Wang, Miaohui; Xie, Weixin; Zhang, Jia; Qin, Jing

doi:10.1109/tii.2020.2973733

Cited by 7 publications

(3 citation statements)

References 31 publications

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“…Conversely, compressing images for storing in memory has no restrictions. It is due to this that the algorithms are executed in non-real time, where there is no need for buffers for the communication channel [2]. Image compression can be categorized into two main types: one is lossless, which contains no loss of image quality and is used for applications where no loss is tolerable, such as medical imaging, scientific research, and satellite imaging, while the other is lossy, which bears the loss in quality and is suitable for applications where losses are acceptable, such as video streaming, web publishing, and social media, etc.…”

Section: Introductionmentioning

confidence: 99%

Fast Linde–Buzo–Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation

Bilal,

Ullah,

Mujahid

et al. 2024

J. Imaging

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Vector quantization (VQ) is a block coding method that is famous for its high compression ratio and simple encoder and decoder implementation. Linde–Buzo–Gray (LBG) is a renowned technique for VQ that uses a clustering-based approach for finding the optimum codebook. Numerous algorithms, such as Particle Swarm Optimization (PSO), the Cuckoo search algorithm (CS), bat algorithm, and firefly algorithm (FA), are used for codebook design. These algorithms are primarily focused on improving the image quality in terms of the PSNR and SSIM but use exhaustive searching to find the optimum codebook, which causes the computational time to be very high. In our study, our algorithm enhances LBG by minimizing the computational complexity by reducing the total number of comparisons among the codebook and training vectors using a match function. The input image is taken as a training vector at the encoder side, which is initialized with the random selection of the vectors from the input image. Rescaling using bilinear interpolation through the nearest neighborhood method is performed to reduce the comparison of the codebook with the training vector. The compressed image is first downsized by the encoder, which is then upscaled at the decoder side during decompression. Based on the results, it is demonstrated that the proposed method reduces the computational complexity by 50.2% compared to LBG and above 97% compared to the other LBG-based algorithms. Moreover, a 20% reduction in the memory size is also obtained, with no significant loss in the image quality compared to the LBG algorithm.

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Section: Introductionmentioning

confidence: 99%

Fast Linde–Buzo–Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation

Bilal,

Ullah,

Mujahid

et al. 2024

J. Imaging

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show abstract

“…With the development of the smart industry, image and video play a key role in many industrial scenarios [1][2][3]. As a result, video coding standards have been used more widely than ever [4]. Although advanced video coding (AVC) was introduced in 2003, it is still used by many applications today due to its fast coding speed [5].…”

Section: Introductionmentioning

confidence: 99%

Transformer-Based Data-Driven Video Coding Acceleration for Industrial Applications

Zhuang

et al. 2022

Mathematical Problems in Engineering

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With the exploding development of edge intelligence and smart industry, deep learning-based intelligent industrial solutions are promptly applied in the manufacturing process. Many intelligent industrial solutions such as automatic manufacturing inspection are computer vision based and require fast and efficient video encoding techniques so that video streams can be processed as quickly as possible either at the edge cluster or over the cloud. As one of the most popular video coding standards, the high efficiency video coding (HEVC) standard has been applied to various industrial scenes. However, HEVC brings not only a higher compression rate but also a significant increase in encoding complexity, which hinders its practical application in industrial scenarios. Fortunately, a large amount of video coding data makes it possible to accelerate the encoding process in the industry. To speed up the video coding process in some industrial scenes, this paper proposes a data-driven fast approach for coding tree unit (CTU) partitioning in HEVC intracoding. First, we propose a method to represent the partition result of a CTU as a column vector of length 21. Then, we employ lots of encoding data produced in normal industry scenes to train transformer models used to predict the partitioning vector of the CTU. Finally, the final partitioning structure of the CTU is generated from the partitioning vector after a postprocessing operation and used by an industrial encoder. Compared with the original HEVC encoder used by some industrial applications, experiment results show that our approach achieves 58.77% encoding time reduction with 3.9% bit rate loss, which indicates that our data-driven approach for video coding has great capacity working in industrial applications.

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“…VFMV images are expected to resolve VAC by dynamically shifting focal planes at different depths for different views [20]. Moreover, VFMV images will contribute to in defect inspection, 3D visual sensing [21], autonomous vehicles, computational photography [22,23], microscopic imaging [24,25], telemedicine and telehealth [26,27], industrial video applications [28,29].…”

Section: Introductionmentioning

confidence: 99%

Varifocal Multiview Images: Capturing and Visual Tasks

Wu¹,

Liu²,

Li³

et al. 2021

Preprint

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Multiview images have flexible field of view (FoV) but inflexible depth of field (DoF). To overcome the limitation of multiview images on visual tasks, in this paper, we present varifocal multiview (VFMV) images with flexible DoF. VFMV images are captured by focusing a scene on distinct depths by varying focal planes, and each view only focused on one single plane. Therefore, VFMV images contain more information in focal dimension than multiview images, and can provide a rich representation for 3D scene by considering both FoV and DoF. The characteristics of VFMV images are useful for visual tasks to achieve high quality scene representation. Two experiments are conducted to validate the advantages of VFMV images in 4D light field feature detection and 3D reconstruction. Experiment results show that VFMV images can detect more light field features and achieve higher reconstruction quality due to informative focus cues. This work demonstrates that VFMV images have definite advantages over multiview images in visual tasks.

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Industrial Applications of Ultrahigh Definition Video Coding With an Optimized Supersample Adaptive Offset Framework

Cited by 7 publications

References 31 publications

Fast Linde–Buzo–Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation

Fast Linde–Buzo–Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation

Transformer-Based Data-Driven Video Coding Acceleration for Industrial Applications

Varifocal Multiview Images: Capturing and Visual Tasks

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