Browsing by Subject "Image blocks"

Now showing 1 - 2 of 2

Open Access
JPEG hardware accelerator design for FPGA
(IEEE, 2007) Duman, Kaan; Çoǧun, Fuat; Öktem, L.
A fully pipelined JPEG hardware accelerator that runs on FPGA is presented. The accelerator is designed interactively in a simulation environment, using a DSP hardware design automation tool chain. The encoder part of the accelerator accepts 8×8 image blocks in a streaming fashion, and outputs the zigzag-scanned, quantized 2-D DCT coefficients of the block. The decoder part accepts zigzag-scanned, quantized DCT coefficients, and outputs reconstructed 8×8 image block. Each part has a throughput of one system clock per pixel per channel. The encoder employs a fast pipelined implementation for 2-D DCT [1]. For the decoder, a new pipelined 2-D IDCT structure is developed. Our IDCT structure is based on an IDCT factorization for software implementation [2], and is inspired by the pipelined DCT structure employed in the encoder. The resource utilization and maximum frequency figures for a particular FPGA target suggest that our accelerator has competitive performance.
Open Access
Microscopic image classification using sparsity in a transform domain and Bayesian learning
(IEEE, 2011) Suhre, Alexander; Erşahin, Tülin; Çetin-Atalay, Rengül; Çetin, A. Enis
Some biomedical images show a large quantity of different junctions and sharp corners. It is possible to classify several types of biomedical images in a region covariance approach. Cancer cell line images are divided into small blocks and covariance matrices of image blocks are computed. Eigen-values of the covariance matrices are used as classification parameters in a Bayesian framework using the sparsity of the parameters in a transform domain. The efficiency of the proposed method over classification using standard Support Vector Machines (SVM) is demonstrated on biomedical image data. © 2011 EURASIP.