BAI Yuhui

PhD graduated
Team : SYEL
Departure date : 01/01/2015

Supervision : Bertrand GRANADO

Compression temps réel de séquences d'images médicales sur des systèmes embarqués

In the field of healthcare, developments in medical imaging are progressing very fast. New technologies have been widely used for the support of patient medical diagnosis and treatment. The mobile healthcare becomes an emerging trend, which provides remote healthcare and diagnostics. By using telecommunication networks and information technology, the medical records including medical imaging and patient's information can be easily and rapidly shared between hospitals and healthcare services. Due to the large storage size and limited transmission bandwidth, an efficient compression technique is necessary. As a medical certificate image compression technique, WAAVES provides high compression ratio while ensuring outstanding image quality for medical diagnosis. The challenge is to remotely transmit the medical image through the mobile device to the healthcare center over a low bandwidth network. Our goal is to propose a high-speed embedded image compression solution, which can provide a compression speed of 10 MB/s while maintaining the equivalent compression quality as its software version.
We first analyzed the WAAVES encoding algorithm and evaluated its software complexity, based on a precise software profiling, we revealed that the complex algorithm in WAAVES makes it difficult to be optimized for certain implementations under very hard constrains, including area, timing and power consumption. One of the key challenges is that the Adaptive Scanning block and Hierarchical Enumerative Coding block in WAAVES take more than 90% of the total execution time. Therefore, we exploited several potentialities of optimizations of the WAAVES algorithm to simplify the hardware implementation. We proposed the methodologies of the possible implementations of WAAVES, which started from the evaluation of software implementation on DSP platforms, following this evaluation we carried out our hardware implementation of WAAVES. Since FPGAs are widely used as prototyping or actual SoC implementation for signal processing applications, their massive parallelism and abundant on-chip memory allow efficient implementation that often rivals CPUs and DSPs.
We designed our WAAVES Encoder SoC based on an Altera's Stratix IV FPGA, the two major time consuming blocks: Adaptive Scanning and Hierarchical Enumerative Coding are designed as IP accelerators. We realized the IPs with two different optimization levels and integrated them into our Encoder SoC. The Hardware implementation running at 100 MHz provides significant speedup compared to the other software implementation including ARM Cortex A9, DSP and CPU and can achieve a coding speed of 10 MB/s that fulfills the goals of our thesis.

Defence : 11/18/2014 - 10h - Site Jussieu 25-26/105

Jury members :

Jean-François NEZAN, professeur des universités, INSA [Rapporteur]
Roberto SARMIENTO, professeur des universités, University of Las Palmas de Gran Canaria [Rapporteur]
Bertrand GRANADO, professeur des universités, Université Pierre et Marie Curie
Olivier ROMAIN, professeur des universités, Université Cergy Pontoise
Sylvain HOCHBERG, Industriel, Société CIRA

2012-2015 Publications