Image Denoising Using Sure-Based Adaptive Thresholding In Directionlet Domain

The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality

Investigations on the structural and operational changes of Ring Seine Fishing Systems of Kerala and its Life Cycle Assessment (lCA)

The study covers theFishing capture technology innovation includes the catching of aquatic animal, using any kind of gear techniques, operated from a vessel. Utilization of fishing techniques varies, depending upon the type of fisheries, and can go from a basic and little hook connected to a line to huge and complex mid water trawls or seines operated by large fishing vessels.The size and autonomy of a fishing vessel is largely determined by its ability to handle, process and store fish in good condition on board, and thus these two characteristics have been greatly influenced by the introduction and utilization of ice and refrigeration machinery. Other technological developments especially hydraulic hauling machinery, fish finding electronics and synthetic twines have also had a major impact on the efficiency and profitability of fishing vessels.A wide variety of fishing gears and practices ranging from small-scale artisanal to advanced mechanised systems are used for fish capture in Kerala. Most important among these fishing gears are trawls, seines, lines, gillnets and entangling nets and traps The modern sector was introduced in 1953 at Neendakara, Shakthikulangara region under the initiative of Indo-Norwegian project (INP). The novel facilities introduced in fishing industry by Indo- Norwegian project accordingly are mechanically operated new boats with new fishing nets. Soon after mechanization, motorization programme gained momentum in Kerala especially in Alleppey, Ernakulam and Kollam districts.