High throughput spatial convolution filters on FPGAs

Digital signal processing (DSP) on field- programmable gate arrays (FPGAs) has long been appealing because of the inherent parallelism in these computations that can be easily exploited to accelerate such algorithms. FPGAs have evolved significantly to further enhance the mapping of these algorithms, included additional hard blocks, such as the DSP blocks found in modern FPGAs. Although these DSP blocks can offer more efficient mapping of DSP computations, they are primarily designed for 1-D filter structures. We present a study on spatial convolutional filter implementations on FPGAs, optimizing around the structure of the DSP blocks to offer high throughput while maintaining the coefficient flexibility that other published architectures usually sacrifice. We show that it is possible to implement large filters for large 4K resolution image frames at frame rates of 30–60 FPS, while maintaining functional flexibility

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

A comparative study of image compress schemes

Image compression is an important and active area of signal processing. All popular image compression techniques consist of three stages: Image transformation, quantization (lossy compression only), and lossless coding (of quantized transform coefficients). This thesis deals with a comparative study of several lossy image compression techniques. First, it reviews the well-known techniques of each stage. Starting with the first stage, the techniques of orthogonal block transformation and subband transform are described in detail. Then the quantization stage is described, followed by a brief review of the techniques for the third stage, lossless coding. Then these different image compression techniques are simulated and their rate-distortion performance are compared with each other. The results show that two-band multiplierless PR-QMF bank based subband image codec outperforms other filter banks considered in this thesis. It is also shown that uniform quantizers with a dead-zone perform best. Also, the multiplierless PR-QMF bank outperforms the DCT based on uniform quantization, but underperforms the DCT based on uniform quantization with a dead-zone