Approximate calculation of 8-point DCT for various scenarios of practical applications

Puchala, Dariusz

doi:10.1186/s13640-021-00557-3

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…To enhance the accuracy of the image processing algorithm, approximate computing plays a major role, in that prediction-based error control was proposed. In DCT picture compression, approximate computation was applied [15]. To assess the various metrics, such as delay, energy usage, and PSNR, a collection of images is compressed.…”

Section: Related Workmentioning

confidence: 99%

Design and Analysis of Multiplexer based Approximate Adder for Low Power Applications

Eamani

Kumar

2023

IJRITCC

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Low power consumption is crucial for error-acceptable multimedia devices, with picture compression approaches leveraging various digital processing architectures and algorithms. Humans can assemble useful information from partially inaccurate outputs in many multimedia applications. As a result, producing exact outputs is not required. The demand for an exact outcome is fading because new innovative systems are forgiving of faults. In the domain where error-tolerance is accepted, approximate computing is a new paradigm that relaxes the requirement for an accurate modeling while offering power, time, and delay benefits. Adders are an essential arithmetic module for regulating power and memory usage in digital systems. The recent implementation and use of approximate adders have been supported by trade-off characteristics such as delay, lower power consumption. This study examines the delay and power consumption of conventional and approximate adders. Also, a simple, fast, and power-efficient multiplexer-based approximate adder is proposed, and its performance outperforms the adders compared with existing adders. The proposed adder can be utilized in error-tolerant and various digital signal processing applications where exact results are not required. The proposed and existing adders are designed using EDA software for the performance calculations. With a delay of 81 pS, the proposed adder circuit reduces power consumption compared to the exact one. The experiment shows that the designed approximate adder can be used to implement circuits for image processing systems because it has a smaller delay and uses less energy.

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Section: Related Workmentioning

confidence: 99%

Design and Analysis of Multiplexer based Approximate Adder for Low Power Applications

Eamani

Kumar

2023

IJRITCC

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“…Consequently, the DCT is the core of multimedia image and video compression techniques such as Joint Photographic Experts Group (JPEG) and Moving Picture Experts Group (MPEG) compression standards [21]. Moreover, the DCT has good decorrelating properties and may be employed to reduce the inherent high correlation that exists between the rows and columns of images [22]. e elements of matrix T of one-dimensional DCT in the case of N-element input vectors can be defined as follows [21]:…”

Section: Discrete Cosine Transformmentioning

confidence: 99%

“…Since the pioneering work by Haweel [20] that explored a DCT approximation requiring only 24 additions, many other approximations have been introduced in the literature. A comparative study for all effective approximations has been analysed in Reference [22].…”

Section: Discrete Cosine Transformmentioning

confidence: 99%

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Fast COVID-19 Detection from Chest X-Ray Images Using DCT Compression

Taher

Haweel

Bastaki

et al. 2022

Applied Computational Intelligence and Soft Computing

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Novel coronavirus (COVID-19) is a new strain of coronavirus, first identified in a cluster with pneumonia symptoms caused by SARS-CoV-2 virus. It is fast spreading all over the world. Most infected people will develop mild to moderate illness and recover without hospitalization. Currently, real-time quantitative reverse transcription-PCR (rqRT-PCR) is popular for coronavirus detection due to its high specificity, simple quantitative analysis, and higher sensitivity than conventional RT-PCR. Antigen tests are also commonly used. It is very essential for the automatic detection of COVID-19 from publicly available resources. Chest X-ray (CXR) images are used for the classification of COVID-19, normal, and viral pneumonia cases. The CXR images are divided into sub-blocks for finding out the discrete cosine transform (DCT) for every sub-block in this proposed method. In order to produce a compressed version for each CXR image, the DCT energy compaction capability is used. For each image, hardly few spectral DCT components are included as features. The dimension of the final feature vectors is reduced by scanning the compressed images using average pooling windows. In the 3-set classification, a multilayer artificial neural network is used. It is essential to triage non-COVID-19 patients with pneumonia to give out hospital resources efficiently. Higher size feature vectors are used for designing binary classification for COVID-19 and pneumonia. The proposed method achieved an average accuracy of 95% and 94% for the 3-set classification and binary classification, respectively. The proposed method achieves better accuracy than that of the recent state-of-the-art techniques. Also, the time required for the implementation is less.

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“…In addition, the use of 88  blocks for DCT and Q is more optimized for hardware than other sizes [24]. To avoid excessive use of memory and resources to split blocks and optimize all functions during video encoding, all equations, including DCT, Q, ME, use a block-based structure 88  .…”

Section: B Motion Estimation and Motion Compensationmentioning

confidence: 99%

Edge Computing-Based SAT-Video Coding for Remote Sensing

et al. 2022

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This paper proposes an edge computing-based video coding implementation on an Earth observation satellite (SAT-video coding), which can encode video using limited resources and the power of mini/microsatellites. SAT-video coding proposes a hardware-related quantization (Q) function, hardware reduction of the motion estimation (ME) method, and simplified entropy coding (EC), which reduces the computation complexity. The hardware-related Q reduces hardware resource and power consumption by 72% and 55%, respectively, compared with traditional Q implementation. The hardware reduction of ME reduces resource use compared with regular ME implementation (59 % of lookup tables [LUTs] and 79% of Registers). The total number of LUTs used for the simplified EC function is also much lower than other EC hardware implementations. The SAT-video encoder IP uses fewer hardware resources, and the power consumption is estimated at 0.0894 W at a high working frequency (125 MHz). The SAT-video encoding speed is 18.95 frames per second for 2560×2560 video. Therefore, the proposed SAT-video coding is an edge computation suitable for micro/minisatellites. The coding efficiency records the highest compression ratio at 33.8, with a peak signal-to-noise ratio of 34.46 dB. With the important task of designing edge computing based on satellite video encoding, these are adequate values for remote sensing video.INDEX TERMS Video compression, remote sensing video, hardware acceleration, satellite.

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Approximate calculation of 8-point DCT for various scenarios of practical applications

Cited by 8 publications

References 17 publications

Design and Analysis of Multiplexer based Approximate Adder for Low Power Applications

Design and Analysis of Multiplexer based Approximate Adder for Low Power Applications

Fast COVID-19 Detection from Chest X-Ray Images Using DCT Compression

Edge Computing-Based SAT-Video Coding for Remote Sensing

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