Hardware Design of 8 × 8 and 16 × 16 2D Discrete Cosine Transform with N/2 Equations for Image Compression

Bichwe, Nikhil C.; Chaurasiya, Rahul Kumar

doi:10.1007/978-3-030-39875-0_26

Cited by 1 publication

(1 citation statement)

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“…Noninvertible transformation enabled with orthogonal transforms that transform from pattern space to feature space with less dimensionality. Orthogonal transforms like walsh-hadamard, discrete-fourier, slant, and Haar were considered for different applications because they have fast computing algorithms [3]- [10] for them. Karhunen-loeve transform (KLT) is optimal with respect to the following: variance distribution [3], Estimation mean-square error criterion [4], [6] and rate-distortion function [6], lacks an algorithm that enables its fast computation [3].…”

Section: Introductionmentioning

confidence: 99%

Reduced encoder time complexity using enhanced adaptive multiple transform selection in versatile video coding

Tummala,

Nalluri

2023

IJEECS

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<span>When compressing a video, the architecture is provided with the width and height of the frame along with the video as input. The multiple transform selection (MTS) techniques are used to compress video. Traditional discrete cosine transforms (DCT) and other trigonometric (sine and cosine) transforms, such as DCT-8 and DST-7, are included in the pool of transforms. For the best outcomes, two additional transforms-DST-2 and DCT-5-were also utilized to compress any remaining video frames. To improve coding effectiveness, peak signal-to-noise ratio (PSNR), and delay, 2D Transforms are broken into 1D Directional Transforms for block sizes ranging from 4×4 to 64×64. The temporal complexity was greatly decreased by adding DST-2 to the existing video test model (VTM). The MTS’s adaptive multiple transform (AMT) scheme already included a pool of transforms, but DST-2 was introduced as a fourth transform. Encoder time complexity was reduced by 22% on average without compromising PSNR and bitrate.</span>

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