Structured lighting techniques have increasingly been employed in underwater imaging. Except for the limitation in underwater illumination, the desire of underwater image acquisition comes from the applicability of removal of the back scattered light, the critical problem of underwater imaging, using structured lighting techniques. This paper presents an approach for underwater image recovery using structured light and CCD camera. By integrating the scanned frame images, we generate an integration image which can be formulated as the convolution of the surface albedo and the illumination function. Thus, underwater image acquisition is addressed as an optimization problem of image recovery and resolved by deconvolution, rather than the traditional geometric manipulation of frame tiling. The significance of the proposed method is that the forward scattering effect in the recovered image is fully eliminated by the integration operation and collection of the forward scattered light enhances the total imaging energy. By means of the structured lighting technique, an algorithm of using virtual aperture to limit the field of view is proposed to eliminate the back scattered light in frame images. Concerned with applicability of using the broad lighting pattern in structured light systems, the coded structured light with binary pseudorandom sequence is introduced, by which the high-frequency details in image recovery can be preserved through deconvolution. The results of underwater experiments are given. INDEX TERMS Structured light, image recovery, elimination of back scattered light, coded structured light.
Structured lighting techniques have increasingly been employed in underwater imaging, where scattering effects cannot be ignored. This paper presents an approach to underwater image recovery using structured light as a scanning mode. The method tackles both the forward scattering and back scattering problems. By integrating each of the sequentially striping illuminated frame images, we generate a synthesized image that can be modeled on the convolution of the surface albedo and the illumination function. Thus, image acquisition is issued as a problem of image recovery by deconvolution. The convolutional model has the advantage of integrating the forward scattering light into a recovered image so as to eliminate image blur. Notably, the removal of the back scattered light from each frame image can be easily realized by a virtual aperture to limit the field of view; the same principle as of the synchronous scanning systems in underwater imaging. Herein, the implementation of the proposed approach is described, and the results of the underwater experiments are presented.
An underwater optical imaging system is indispensable for many oceanic engineering tasks, yet still plagued by poor visibility conditions. The serious degradation of underwater image results from light scattering and absorption. Removal of the backscattered light is the focus issue of underwater imaging technology to improve the image visibility, particularly in turbid water. In this paper, we present an approach for underwater image recovery using structured light imaging and flood light imaging to compose a combined imaging model with which the backscatter component is completely offset. The convolutional image is obtained using the structured light scanning imaging mode where the backscatter intensity is proportional to that of the flood light image with an unknown scale parameter. An algorithm to refine the matching of the backscatter components of both the convolutional image and the flood light image is proposed. Thus, subtraction of both images gives rise the combined imaging model without the backscatter component. Consequently, image restoration is completed by employing the deconvolution process. Results of underwater experiments are given.
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