Architecture-aware optimization strategies in real-time image processing
In the field of image processing, many applications require real-time execution, particularly those in the domains of medicine, robotics and transmission, to name but a few. Recent technological developments have allowed for the integration of more complex algorithms with large data volume into embe...
Otros Autores: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
London, [England] ; Hoboken, New Jersey :
ISTE
2017.
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Edición: | 1st edition |
Colección: | Digital signal and image processing series.
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Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630661206719 |
Tabla de Contenidos:
- Cover
- Half-Title Page
- Title Page
- Copyright Page
- Contents
- Preface
- 1. Introduction of Real-time Image Processing
- 1.1. General image processing presentation
- 1.2. Real-time image processing
- 2. Hardware Architectures for Real-time Processing
- 2.1. History of image processing hardware platforms
- 2.2. General-purpose processors
- 2.3. Digital signal processors
- 2.4. Graphics processing units
- 2.5. Field programmable gate arrays
- 2.6. SW/HW codesign of real-time image processing
- 2.7. Image processing development environment description
- 2.8. Comparison and discussion
- 3. Rapid Prototyping of Parallel Reconfigurable Instruction Set Processor for Efficient Real-Time Image Processing
- 3.1. Context and problematic
- 3.2. Related works
- 3.3. Design exploration framework
- 3.4. Case study: RISP conception and synthesis for spatial transforms
- 3.4.1. Digital DCT algorithm implementations
- 3.4.2. Rapid prototyping of DCT RISP conception
- 3.4.3. RISP simulation and synthesis for 2D-DCT
- 3.5. Hardware implementation of spatial transforms on an FPGA-based platform
- 3.6. Discussion and conclusion
- 4. Exploration of High-level Synthesis Technique
- 4.1. Introduction of HLS technique
- 4.2. Vivado_HLS process presentation
- 4.2.1. Control and datapath extraction
- 4.2.2. Scheduling and binding
- 4.3. Case of HLS application: FPGA implementation of an improved skin lesion assessment method
- 4.3.1. KMGA method description
- 4.3.2. KMGA method optimization
- 4.3.3. HCR-KMGA implementation onto FPGA using HLS technique
- 4.3.4. Implementation evaluation experiments
- 4.4. Discussion
- 5. CDMS4HLS: A Novel Source-To-Source Compilation Strategy for HLS-Based FPGA Design
- 5.1. S2S compiler-based HLS design framework
- 5.2. CDMS4HLS compilation process description
- 5.2.1. Function inline.
- 5.2.2. Loop manipulation
- 5.2.3. Symbolic expression manipulation
- 5.2.4. Loop unwinding
- 5.2.5. Memory manipulation
- 5.3. CDMS4HLS compilation process evaluation
- 5.3.1. Performances improvement evaluation
- 5.3.2. Comparison experiment
- 5.4. Discussion
- 6. Embedded Implementation of VHR Satellite Image Segmentation
- 6.1. LSM description
- 6.1.1. Background
- 6.1.2. Level set equation
- 6.1.3. LBM solver
- 6.2. Implementation and optimization presentation
- 6.2.1. Design flow description
- 6.2.2. Algorithm analysis
- 6.2.3. Function inline
- 6.2.4. Loop manipulation
- 6.2.5. Symbol expression manipulation
- 6.2.6. Loop unwinding
- 6.3. Experiment evaluation
- 6.3.1. Parameter configuration
- 6.3.2. Function verification
- 6.3.3. Optimization evaluation
- 6.3.4. Performance comparison
- 6.4. Discussion and conclusion
- 7. Real-time Image Processing with Very High-level Synthesis
- 7.1. VHLS motivation
- 7.2. Image processing from Matlab to FPGA-RTL
- 7.3. VHLS process presentation
- 7.3.1. Dynamic variable
- 7.3.2. Operation polymorphism problem
- 7.3.3. Built-in function problem
- 7.4. VHLS implementation issues
- 7.4.1. Work flow
- 7.4.2. Intermediate code versus RTL
- 7.4.3. SSC versus HLS
- 7.4.4. Verification and evaluation
- 7.5. Future work for real-time image processing with VHLS
- Bibliography
- Index
- Other titles from iSTE in Digital Signal and Image Processing
- EULA.