Listening to nature : techniques for large-scale monitoring of ecosystems using acoustics

Climate change and human activity are subjecting the environment to unprecedented rates of change. Monitoring these changes is an immense task that demands new levels of automated monitoring and analysis. We propose the use of acoustics as a proxy for the time consuming auditing of fauna, especially for determining the presence/absence of species. Acoustic monitoring is deceptively simple; seemingly all that is required is a sound recorder. However there are many major challenges if acoustics are to be used for large scale monitoring of ecosystems. Key issues are scalability and automation. This paper discusses our approach to this important research problem. Our work is being undertaken in collaboration with ecologists interested both in identifying particular species and in general ecosystem health

Intrinsic correspondence using statistical signature-based matching for 3D surfaces

A wide variety of applications including object recognition and terrain mapping, rely upon automatic three dimensional surface modelling. The automatic correspondence stage of the modelling process has proven challenging. Intrinsic correspondence methods determine matching segments of partially overlapping 3D surfaces, by using properties intrinsic to the surfaces. These methods do not require initial relative orientations to begin the matching procedures. Hence, intrinsic methods are well-suited for automatic matching

Visual Quality Assessment of Watermarked Medical Images

Increasing transmission of medical images across multiple user systems raises concerns for image security. Hiding watermark information in medical image data files is one solution for enhancing security and privacy protection of data. Medical image watermarking however is not a widely studied area, due partially to speculations on loss in viewer performance caused by degradation of image information. Such concerns are addressed if the amount of information lost due to watermarking can be kept at minimal levels and below visual perception thresholds. This paper describes experiments where three alternative visual quality metrics were used to assess the degradation caused by watermarking medical images. Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) medical images were watermarked using different methods: Block based Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) with various embedding strengths. The visual degradation of each watermarking parameter setting was assessed using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Measure (SSIM) and Steerable Visual Difference Predictor (SVDP) numerical metrics. The suitability of each of the three numerical metrics for medical image watermarking visual quality assessment is noted. In addition, subjective test results from human observers are used to suggest visual degradation thresholds

A comparison of DCT and DWT block based watermarking on medical image quality

Hiding watermark information in medical image data files is one method of enhancing security and protecting patient privacy. However the research area of medical image watermarking has not been particularly active, partly due to concerns that any distortion could affect the diagnostic value of the medical image. These concerns can be addressed by ensuring that any image changes are kept below visual perception thresholds. In this paper the effects of image watermarking and common image manipulations are measured using the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Measure (SSIM) and Steerable Visual Difference Predictor (SVDP) numerical metrics. Two methods of block based watermarking are compared: the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). To ensure a fair comparison a 128-pixel block size is used which allows an identical amount of information to be embedded for each method (3072 bits multiplied by embedding strength). The results suggest that although the two methods are similar, the DCT method is preferable if localization of changes is required. If localization is not required the DWT method is supported