Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/15637
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dc.contributor.authorAppina, Balasubramanyamen_US
dc.date.accessioned2025-02-04T14:30:52Z-
dc.date.available2025-02-04T14:30:52Z-
dc.date.issued2025-
dc.identifier.citationBhanuprakash Reddy Konduru, L., Pudi, V., & Appina, B. (2025). Design of Low-Complexity Quantized Compressive Sensing Using Measurement Predictive Coding. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. Scopus. https://doi.org/10.1109/TVLSI.2024.3438249en_US
dc.identifier.issn1063-8210-
dc.identifier.otherEID(2-s2.0-85216116636)-
dc.identifier.urihttps://doi.org/10.1109/TVLSI.2024.3438249-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/15637-
dc.description.abstractBlock-based compressive sensing (BCS) has evolved as a promising method for smart devices with limited bandwidth and computing capabilities, striking a balance between image/video quality and transmission efficiency. Despite its advantages, BCS falls short in reducing bitrate compared with traditional acquisition systems, because it increases the number of bits per measurement, which leads to high storage and transmission costs. In this context, we propose a measurement predictive coding (MPC) along with the quantization method in integration with BCS named BCS-MPCen_US
dc.description.abstracthere, we have performed the quantization with bit shifts only instead of binary division. The proposed method reduces the number of bits per compressive sensing (CS) measurement as well as the transmission of the quantization step size. Furthermore, it reduces the latency and hardware resources. The proposed method improved on average +3.44 to +8.28 dB in PSNR over the current works. From the synthesis results, the proposed BCS-MPC method requires 26.11%, 18.89%, and 82.53% less area, power, and delay over the existing work. We have achieved a reduction in delay with bit-shift operations. © 1993-2012 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceIEEE Transactions on Very Large Scale Integration (VLSI) Systemsen_US
dc.subjectCompressive sensing (CS)en_US
dc.subjectintrapredictionen_US
dc.subjectintrapredictive codingen_US
dc.subjectJPEG compressionen_US
dc.subjectpredictive codingen_US
dc.titleDesign of Low-Complexity Quantized Compressive Sensing Using Measurement Predictive Codingen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Electrical Engineering

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