Electrical Science & Engineering

High-Throughput CBC Mode Crypto Circuit

2023-04-12T13:51:44+08:00

The objective of this study is to investigate a high-throughput cipher-block chaining (CBC) mode crypto circuit, which can be embedded in commercial home gateways or switches/routers. Concurrently, the area efficiency of block ciphers can be improved as well. However, the CBC mode encounters the problem of data dependency. To solve this issue, a data scheduling mechanism of network packets is proposed to eliminate the data dependency of input data for CBC mode pipelined crypto engines. The proposed CBC mode architecture can be applied to advanced encryption standards (AES), triple data encryption standards (3DES), and other block ciphers. In addition, to increase the throughput, deeply pipelined AES-CBC and 3DES-CBC circuits with balanced paths are proposed. With the proposed scheduling and pipelined circuits, the authors can effectively encrypt the packet data of multiple network channels at the same time. Using the proposed architecture, throughputs of 137.8 and 44.75 Gbps using a copy of pipelined AES-CBC and 3DES-CBC circuits can be achieved in TSMC 45 nm and TSMC 130 nm processes, respectively.

Satellite Image Enhancement Using Histogram Equalization

2023-02-23T14:53:31+08:00

Image enhancement is an indispensable technique in improving the quality, brightness, contrast and clarity of satellite images. The object that appears in images and variation caused by shadow, occlusion, camouflage in satellite images are the fundamental challenges posed by image enhancement techniques. The aim of this research work was to enhance satellite images of Sambisa using histogram equalization technique. MATLAB 2021 was used to implement the experiment. The results show that histogram equalization method has an excellent processing effect and it improved the brightness, contrast and clarity of the images as compared original images and the enhanced images.

Wavelet Transform Technique Applied to Satellite Image Denoising

2023-02-23T14:53:21+08:00

Satellite images either digital or analog must have certain elements that are accidentally introduced during the processing of capturing as a result of weather or system sensor known as electronic noise. However, several attempts and advances have been made by academicians, industries and intelligent security agencies to remove this noise. It has been a nagging problem in the area of computer vision, image processing and artificial intelligence to denoise satellite images and noise removal is among the significant components in satellite image analysis. The aim of this research work was to denoise the satellite image of Sambisa forest using the wavelet transform technique. Satellite images of Sambisa forest captured by Landsat satellite in 2007, 2013, 2014, 2019 and 2021 respectively with their associated Geo-referenced 11.2503° N Longitude and 13.4167° E Latitude were downloaded from the United States Geological Survey (USGS) website. The images are acquired as Zipped Geo-referenced Tagged Image File Format (GeoTIFF). Color Composite bands of natural colors (bands 2, 3 and 4) are combined using the ArcGIS software and RGB image were obtained. Wavelet transforms denoising technique was used to filter noise from the images, which was implemented using the wdenoise2() function in MATLAB 2021.