Ultra high speed image processing techniques

Packaging techniques for ultra high speed image processing were developed. These techniques involve the development of a signal feedthrough technique through LSI/VLSI sapphire substrates. This allows the stacking of LSI/VLSI circuit substrates in a 3 dimensional package with greatly reduced length of interconnecting lines between the LSI/VLSI circuits. The reduced parasitic capacitances results in higher LSI/VLSI computational speeds at significantly reduced power consumption levels

Graph Spectral Image Processing

Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2D grid, if one can design an appropriate underlying graph connecting pixels with weights that reflect the image structure, then one can interpret the image (or image patch) as a signal on a graph, and apply GSP tools for processing and analysis of the signal in graph spectral domain. In this article, we overview recent graph spectral techniques in GSP specifically for image / video processing. The topics covered include image compression, image restoration, image filtering and image segmentation

Intelligent image processing techniques for structuring a visual diary

The SenseCam is a small wearable personal device which automatically captures up to 3,500 images per day. This yields a very large personal collection of images or in a sense, a diary of a person's day. Over one million images will need to be stored each year, therefore intelligent techniques are necessary for the effective searching and browsing of this image collection for important or significant events in a person's life, and one of the issues is how to detect and then relate similar events in a lifetime. This is necessary in order to detect unusual or once-off events, as well as determining routine activities. This poster will present the various sources of data that can be collected with a SenseCam device, and also other sources that can be collected to compliment the SenseCam data sources. Different forms of image processing that can be carried out on this large set of images will be detailed, specifically how to detect what images belong to individual events, and also how similar various events are to each other. There will be hundreds of thousands of images of everyday routines; as a result more memorable events are quite likely to be significantly different to other normal reoccurring events

Image Segmentation and Classification of Marine Organisms

To automate the arduous task of identifying and classifying images through their domain expertise, pioneers in the field of machine learning and computer vision invented many algorithms and pre-processing techniques. The process of classification is flexible with many user and domain specific alterations. These techniques are now being used to classify marine organisms to study and monitor their populations. Despite advancements in the field of programming languages and machine learning, image segmentation and classification for unlabeled data still needs improvement. The purpose of this project is to explore the various pre-processing techniques and classification algorithms that help cluster and classify images and hence choose the best parameters for identifying the various marine species present in an image

Segmentation techniques for image processing

Je několik metod pro segmentaci obrazu. Vhodnou volbou metody, dle vstupního obrazu a předpokládaných výsledků, se dá dosáhnout poměrně dobrých výsledků. Při segmentaci se využívá nejen jedna metoda, ale většinou více algoritmů např. pro odstranění šum atp., aby se dosáhlo co nejlepších výsledků. A to metodami jako jsou prahování, hledání oblastí nebo metody založené na hledání hran v obraze. Šum se odstraňuje pomocí různých filtrů, jako např. Gaussovým, mediánovým atp. Lze využít také např. dolní propust. Segmentace obrazu mean-shift, k-mean, watershed a pyramidová segmentace provedená pomocí metod z knihovny OpenCV.For image segmentation are used several methods. Good results can be achieved by the correct choice of method. Best results are using more methods together. Methods such as thresholding, the search area or methods founded on edge detection in an image. We can use different filters for noise removal. For example Gaussian, median, etc. Lowpass filter can also be used. Image segmentation Mean Shift, K-mean, watershed and pyramid segmentation performed by using methods from the OpenCV library.

CLD-shaped Brushstrokes in Non-Photorealistic Rendering

Rendering techniques based on a random grid can be improved by adapting brushstrokes to the shape of different areas of the original picture. In this paper, the concept of Coherence Length Diagram is applied to determine the adaptive brushstrokes, in order to simulate an impressionist painting. Some examples are provided to instance the proposed algorithm.Comment: Keywords: Image processing, Non-photorealistic processing, Image-based rendering Coherence Length Diagra

Experimental study of digital image processing techniques for LANDSAT data

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections