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A study of satellite imagery over the Philippines undertaken as part of the US Office of Naval Research Philippine Straits Experiment (PhilEx) found significant high-frequency nonlinear internal wave activity in the waters around the Philippine Archipelago. Along with previously known nonlinear internal wave occurrence in the Sulu Sea and the Sulu Archipelago, the study found new areas of activity near Surigao Strait, within Butuan and Macajalar Bays along the northern coast of Mindanao in the southeastern Bohol Sea, in the Samar Sea, and at the shelf break at the northern end of the Sulu Sea between Palawan and Panay islands. Signatures in the imagery show that the surface expression of internal waves around the Philippines span a considerable spatial scale, from large solitary waves in the Sulu Sea (10-km scale) to very fine (10-m scale) wave packets found in Butuan Bay. This paper presents examples and discusses the characteristics of the nonlinear internal wave signatures observed in synthetic aperture radar and optical sunglint satellite imagery from around the Philippines.

On this paper, wavelet analysis has been used for internal wave detection in ERS SAR and ASTER images data over Tsushima strait, southwest of Japan, during 1993-2004 period. Various wavelet transforms, such as Haar wavelet, Symlet wavelet, Coif wavelet, Daubechies wavelet, and Discreet Meyer wavelet, are tested comparably with different level of synthesize image on horizontal, diagonal, and vertical detail, and approximation to study the internal wave characteristic in image. Internal wave features were detected as elongated pattern in image with higher wavelet coefficient (>36) than sea surface (litlle than 10) on horizontal and vertical detail coefficient of image transforms at level 2-5. The decomposition image shows the tendency that the decomposition of internal wave feature using wavelet transform tends to follow the wavelet function. This may reduced the height of leading wave. Smoother result of internal wave shape can be formed using higher scale resolution of image and higher number of vanishing moments such as Daubechies waveletdb5, Symlet wavelet-sym5, and Discrete Meyer wavelet. The compactly supported wavelet function with orthogonal basis with scale function and FIR filter, such as discrete Meyer function is proposed for smoothness of feature, space save coding, and to avoid depashing in image. So far, the detection processes were performed well on the internal waves data that occurred at north coast off Kitakyushu and NW/W/SW/E coast off Tsushima Island on June to September period whose lengths were detected between 6-28 km and wavelength between 120m-1.28km. The directions of internal wave propagation were varied between NW-SW at eastern channel and N-SW at western channel of Tsushima Strait. Keywords: wavelet analysis, SAR image, optical image, internal wave.

In this paper, wavelet transform based on dyadic scales and spatial location have been used for internal wave detection in SAR image. It performed by using multi resolution analysis of image for feature detection and image enhancement. Wavelet transform uses local analysis to analyze a shorter region in image in time and scale data allows precise information than time and frequency region analysis such as Fourier analysis. Internal wave is observed in SAR image by effect of Bragg scattering process in sea surface that represents the meso-scale feature of sea processes. SAR image data is used considering to the effectiveness of large scales area monitoring on near real time data. Internal waves were observed in ERS-1 per 2 SAR images data over Lombok Strait during 1996-2001 period using 2D Symlet analysis for the symmetric extension of data at the image boundaries, to prevent discontinuities by a periodic wrapping of data in fast algorithm and space-saving code. Lombok Strait is chosen as study area because this strait is a major passage of the flow from Pacific Ocean to Indonesian seas (ARLINDO) and passage of Indian Ocean Kelvin wave to Makassar Strait. Keyword: SAR image, internal wave, wavelet analysis.