Browsing by Subject "high level languages"

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Access status: Open Access ,
FPGA-based DVCPRO HD decoder implementation using impulse C
(Wydawnictwa AGH, 2013) Cichoń, Sławomir; Gorgoń, Marek
High-level languages (HLL) for defining hardware implementation are important in both academic and commercial research. Impulse C could be an example of such language. This environment provides a programming model and library of functions for parallel applications, targeting FPGA-based platforms with the ability to partition the algorithm between software and hardware. This article’s aim is to briefly describe DVCPRO HD, one of the intra-frame video-coding algorithms widely used in consumer equipment. DVCPRO HD is a DCT -based lossy video coding algorithm which uses variable-length coding (VLC) and run-length encoding (RLE) to achieve a 5:1 compression ratio. This paper presents DVCPRO HD video-coding-standard principles as well as decoder implementation working in real-time, compliant with the afore-mentioned standard and implemented in Impulse C. According to the authors’ knowledge, the presented solution is the first FPGA implementation of this coding standard which includes all three VLC stages of data re-arrangement. What is more, this is the first DVCPRO HD implementation which utilizes Impulse C.
Access status: Open Access ,
Modelowanie i realizacja algorytmów wideodetekcji na platformie FPGA
(Wydawnictwa AGH, 2006) Gorgoń, Marek; Pawlik, Piotr; Jabłoński, Mirosław; Przybyło, Jaromir
In the present paper the background generation and motion detection algorithms, which are of key importance for the implementation of videodetection, has been presented. A modification of the background generation algorithm, allowing for a proper algorithm functioning at medium and high traffic conditions, has been proposed. An adaptation of the algorithm for implementation in the reprogrammable device has been presented. A modification of the SAD algorithm, used for motion detection has been introduced. The modification allows for unrestricted defining of 32 Regions of Interest of irregular shape and structure in the analyzed image. It gives a capability to conduct the calculation in independent and parallel manner for particular, user-defined, active videodetection regions.