Comparative evaluation of image compression techniques

Harikrishnan, N B; Menon, Vignesh V; Nair, Manoj Sajeev; Narayanan, Gayathri

doi:10.1109/icammaet.2017.8186637

Cited by 7 publications

(3 citation statements)

References 4 publications

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“…Conversely, content with high temporal complexity may benefit from a lower resolution, as rapid changes between frames can limit the perceptual benefit of higher spatial detail. This paper uses seven DCT-energy-based features [20,21]: {𝐸 Y , ℎ, 𝐿 Y , 𝐸 U , 𝐿 U , 𝐸 V , 𝐿 V } as the content complexity features of video segments.…”

Section: Spatiotemporal Complexity Feature Extractionmentioning

confidence: 99%

Energy-efficient Adaptive Video Streaming with Latency-Aware Dynamic Resolution Encoding

Menon,

Premkumar,

Rajendran

et al. 2024

Proceedings of the 3rd Mile-High Video Conference on ZZZ

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Traditional per-title encoding schemes aim to optimize encoding resolutions to deliver the highest perceptual quality for each representation. However, keeping the encoding time within an acceptable threshold for a smooth user experience is important to reduce the carbon footprint and energy consumption on encoding servers in video streaming applications. Toward this realization, we introduce an encoding latency-aware dynamic resolution encoding scheme (LADRE) for adaptive video streaming applications. LADRE determines the encoding resolution for each target bitrate by utilizing a random forest-based prediction model for every video segment based on spatiotemporal features and the acceptable target latency. Experimental results show that LADRE achieves an overall average quality improvement of 0.58 dB PSNR and 0.43 dB XPSNR while maintaining the same bitrate, compared to the HTTP Live Streaming (HLS) bitrate ladder encoding of 200 s segments using the VVenC encoder, when the encoding latency for each representation is set to remain below the 200 s threshold. This is accompanied by a 84.17 % reduction in overall encoding energy consumption. CCS CONCEPTS• Information systems → Multimedia streaming.

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Section: Spatiotemporal Complexity Feature Extractionmentioning

confidence: 99%

Energy-efficient Adaptive Video Streaming with Latency-Aware Dynamic Resolution Encoding

Menon,

Premkumar,

Rajendran

et al. 2024

Proceedings of the 3rd Mile-High Video Conference on ZZZ

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show abstract

“…Feature extraction: In live streaming applications, selecting low-complexity features is critical to ensure low-latency video streaming without disruptions. In this paper, the optimized CRF (ĉ) is determined as a function of the spatial and temporal complexity metrics (E and h) [2,12,13] based on DCT energy [14], the target bitrate (b), resolution (r) and framerate (f ). The block-wise texture of each frame is defined as:…”

Section: Etps Architecturementioning

confidence: 99%

ETPS: Efficient Two-Pass Encoding Scheme for Adaptive Live Streaming

Menon

Amirpour

Ghanbari

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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In two-pass encoding, also known as multi-pass encoding, the input video content is analyzed in the first-pass to help the second-pass encoding utilize better encoding decisions and improve overall compression efficiency. In live streaming applications, a single-pass encoding scheme is mainly used to avoid the additional first-pass encoding run-time to analyze the complexity of every video content. This paper introduces an Efficient low-latency Two-Pass encoding Scheme (ETPS) for live video streaming applications. In this scheme, Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features for every video segment are extracted in the first-pass to predict each target bitrate's optimal constant rate factor (CRF) for the second-pass constrained variable bitrate (cVBR) encoding. Experimental results show that, on average, ETPS compared to a traditional two-pass average bitrate encoding scheme yields encoding time savings of 43.78% without any noticeable drop in compression efficiency. Additionally, compared to a single-pass constant bitrate (CBR) encoding, it yields bitrate savings of 10.89% and 8.60% to maintain the same PSNR and VMAF, respectively.

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“…It generally works on the function that integrates to a zero waving over the x-axis and also results in better values over the other algorithms. Based on the wavelet transform, there are many other forms of transforms derived such as Haar wavelet (Harikrishnan et al, 2017) that isolate the image into segments, and the detail is achieved through averaging and differencing. Daubechies (Nagendran & Vasuki, 2019) proposed wavelet (dB1, dB4) which focused on dividing into constituents namely split, prediction, and update method.…”

Section: Related Workmentioning

confidence: 99%

A Metaheuristic Approach for Tetrolet-Based Medical Image Compression

Saravanan

Juliet

2021

Journal of Cases on Information Technology

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Over recent times, medical imaging plays a significant role in clinical practices. Storing and transferring the huge volume of images becomes complicated without an efficient image compression technique. This paper proposes a compression algorithm that uses a Haar based wavelet transform called Tetrolet transform, which reduces the noise on the input images and decomposes with a 4 x 4 blocks of equal squares called tetrominoes. It opts for a decomposing using optimal scheme for achieving the input image into a sparse representation which gives a much-detailed performance for texture and edge information better than wavelet transform. Set Partitioning in Hierarchical Trees (SPIHT) is used for encoding the significant coefficients to achieve efficient image compression. It has been investigated with various metaheuristic algorithms. Experimental results prove that the proposed method outperforms the other transform-based compression in terms of PSNR, CR, and Complexity. Also, the proposed method shows an improved result with another state of work.

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Comparative evaluation of image compression techniques

Cited by 7 publications

References 4 publications

Energy-efficient Adaptive Video Streaming with Latency-Aware Dynamic Resolution Encoding

Energy-efficient Adaptive Video Streaming with Latency-Aware Dynamic Resolution Encoding

ETPS: Efficient Two-Pass Encoding Scheme for Adaptive Live Streaming

A Metaheuristic Approach for Tetrolet-Based Medical Image Compression

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