Parallel Pixel Processing And Filtering Architectures For Image Processing In Verilog For Real-Time Applications
- DOI
- 10.2991/978-94-6463-858-5_207How to use a DOI?
- Keywords
- Parallel Processing; AXI; Pixel Caches; FSM; Hardware acceleration
- Abstract
Parallel Pixel Processing and Filtering Architectures for Image Processing in Verilog (PPPFA). The article discusses image processing using hardware acceleration with focus on the systems which process grayscale images independently of color images. The architecture for processing grayscale images applies 512 × 512 grayscale image processing by spatial convolution-based filtering and edge detection with optimizations based on parallelism, pixel caching, and AXI4-based DMA to ensure fast data movement. For chromatic images, a Verilog-based implementation processes two pixels concurrently with a custom state machine accepting an input of 768x512 pixel image. It carries out operations such as addition and subtraction of brightness, thresholding, inversion, and black-and-white conversion to facilitate effective real-time image manipulations.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Sirasanagandla Bhavyesh AU - Akshay Kondru AU - Saliganti Yashwanth AU - K. Jamal AU - Kiran Mannem AU - M. Suneetha PY - 2025 DA - 2025/11/04 TI - Parallel Pixel Processing And Filtering Architectures For Image Processing In Verilog For Real-Time Applications BT - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025) PB - Atlantis Press SP - 2478 EP - 2493 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-858-5_207 DO - 10.2991/978-94-6463-858-5_207 ID - Bhavyesh2025 ER -