RL-SPIHT: Reinforcement Learning-Based Adaptive Selection of Compression Ratios for 1-D SPIHT Algorithm [PDF]
IEEE Access, 2021 In recent years, deep learning technologies have been actively used in various applications. In particular, networks trained using reinforcement learning (RL) are widely exploited for auxiliary tasks in various multimedia frameworks, including image ...
Jin Shin, Hyun Kim
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Optimal Relay Selection using jellyfish Optimization Algorithm for Image Transmission over Multiuser Cooperative Communication Networks [PDF]
JES: Journal of Engineering Sciences, 2023 A recent study and research have shown that the relay selection schemes for cooperative communication can achieve full cooperative diversity gains and still maintains energy efficiency.
fatma mohamed +2 more
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A Multiresolutionnal Coding Method Based on SPIHT [PDF]
Signal Processing: Image Communication, 2001 In this work, we incorporate a multiresolutional coding functionality into the SPIHT algorithm [1]. The multiresolutional coding can be considered as a kind of the region of interest (ROI) coding with multiple regions of interest. Therefore, the ROI coding proposed by authors can be extended for the multiresolutional functionality without any cost in ...
Park, Keun-hyeong +2 more
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PERFORMANCE ANALYSIS OF IMAGE COMPRESSION BASED ON FAST FRACTIONAL WAVELET TRANSFORM COMBINED WITH SPIHT FOR MEDICAL IMAGES [PDF]
ICTACT Journal on Image and Video Processing, 2018 Fast Fractional Wavelet Transform (FFWT) is an orthogonal linear transform called as decomposed signals in terms of chirps transform. This transform is used for signal and image compression and is based on Eigen value decomposition.
K Ezhilarasan +2 more
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Robust image transmission performed by SPIHT and turbo-codes [PDF]
Serbian Journal of Electrical Engineering, 2008 This work describes the method for providing robustness to errors from a binary symmetric channel for the SPIHT image compression. The source rate and channel rate are jointly optimized by a stream of fixed-size channel packets. Punctured turbo codes are
Lakhdar Moulay Abdelmounaim +2 more
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TWO-STEP PROVIDING OF DESIRED QUALITY IN LOSSY IMAGE COMPRESSION BY SPIHT
Радіоелектронні і комп'ютерні системи, 2020 Image information technology has become an important perception technology considering the task of providing lossy image compression with the desired quality using certain encoders Recent researches have shown that the use of a two-step method can ...
Fangfang Li +2 more
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Fully spatial and SNR scalable, SPIHT-based image coding for transmission over heterogenous networks
Journal of Telecommunications and Information Technology, 2003 This paper presents a fully scalable image coding scheme based on the set partitioning in hierarchical trees (SPIHT) algorithm. The proposed algorithm, called fully scalable SPIHT (FS-SPIHT), adds the spatial scalability feature to the SPIHT algorithm ...
Habibollah Danyali
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Comparison of Effects of Entropy Coding Schemes Cascaded with Set Partitioning in Hierarchical Trees
Mehran University Research Journal of Engineering and Technology, 2018 WT (Wavelet Transform) is considered as landmark for image compression because it represents a signal in terms of functions which are localized both in frequency and time domain.
Ali Iqbal +4 more
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Enhanced SPIHT Algorithm with Pipelined Datapath Architecture Design
Electrica, 2019 Set partitioning in hierarchical trees(SPIHT) is an efficient algorithm which is used for the image compressionwidely. SPIHT operates sequentially so, its parallel implementation isdifficult.
Serap Cekli, Ali Akman
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Algorithmic modifications to SPIHT
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002 This paper proposes several low complexity algorithmic modifications to the SPIHT (set partitioning in hierarchical trees) image coding method of Said and Pearlman (1996). The modifications exploit universal traits common to the real world images. Approximately 1-2% compression gain (bit rate reduction for a given mean squared error) has been obtained ...
Ulug Bayazit, William A. Pearlman
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