The Research Of Underwater Image Enhancement And Restoration

Digital image processing technology has achieved remarkable results in many areas, but the study of underwater image processing is rarely effective, which is due to the environment of underwater imaging is much more complex than on land^[1]. Although the ocean optics research has always been studied for a long time, it was also ignored in a long term because of the physical limitations that the attenuation when light transmited in the water. Over the last decade, the rapid growth of demand for ocean exploration and development is the mainly driving force of underwater vision. The high-resolution visual model has the advantages which can not be replaced with the traditional sonar, and the development of computer vision makes the ocean underwater exploration to get more and more applications. However, the method to improve the quality of underwater image processing technology can still is far from meeting the requirements of applications.The key factor except absorption of water medium is scattering effect of suspended particles. Because of the absence of light source, imaging system must rely on the active lighting pattern. Reflection light of illumination is scattered when it transmits from object to the sensor, which is called forward scattering and it causes the image blur. According to ocean optics’small-angle scattering theory, we can use point spread function （PSF） or optical transfer function （OTF） to describe the forward scattering effect. Before reaching the target, the illumination rays are also scattered by the same water body to form backward scattering, and then the back-scattering is received by the sensor. Backscattering effect occur a "fog" background in the underwater image, which results in the contrast of the image decreased. The combined action of backscattering and forward scattering can lead the underwater image degraded seriously, which is the main reason to limit the distance of underwater observation. While increasing the illumination power can increase the intensity of object reflected light, but the intensity of backscattering is increased too, so the image contrast can not be improved. Therefore, the image processing technology is the necessary means to improve underwater imaging system.In this paper, the method of improving underwater image is discussed from the two aspects, which are image enhancement and image restoration. And the main study of the thesis are listed as follows:1. We proposed a simplified multi-layer transfer model to formulate both the PSF and the statistics of backscattering. In the previous methods of underwater image restoration, the model of PSF was acquired according to the theory of underwater small-angle scattering and experience formula. And the value description was acquired by the image feature extraction of sensor. However these methods did not describe the backscattering quantitatively, which is the important factor to cause image quality degraded. Based on the theoretical analysis and experimental results, we established a new description method of scattering layer-transmission proceeding from the physical mechanism of backscattering and forward scattering. With separating the water body between object and receiver into many independent scattering units and regarding the each scattering unit as an output of each linear subsystem, a simplified model of PSF was derived and the statistical description of backscattering noise was also gained on the basis. The model provided a framework of principles for underwater image enhancement and restoration in this study. So it is the main innovation of this article.2. We studied the enhancement methods for restraining the backscattering noise in the paper. The traditional image denoising methods focused on the irrelevant white noise usually. The theoretical analysis and experimental results of this paper showed that the backscattering signal was composed of the direct component and random fluctuation noise. Excluding the impact of the direct component, the random fluctuation noise showed a strong coherence, and its basic characteristics was that the energy of backscattering noise was concentrated in low frequency. The reason, as we described in the scattering multi-layer transfer model we proposed, was that backscattering was a superposition of the multi-scattering signals through the low-pass filter corresponding to the different length water. Therefore, it did not suppressing the backscattering noise of underwater images by using the existing denoising methods directly. In the study of the existing wavelet denoising method that was applied to underwater images, although the high-frequency noise components can be inhibited, the low-frequency of noise which is the main noise and overlaps with the object signal still can not be suppressed. Our conclusion is that the principle of underwater image backscattering-noise suppression is high-pass filter instead of the low-pass filter principle in the traditional denoising methods. Based on this conclusion, we presented a method to suppress the backscattering noise by using the method of combining wavelet denoising with high-pass filtering and traditional image enhancement filtering.3. We proposed an underwater image restoration method based on estimation. The theory of image restoration provided a schematic framework in order to solve the problem of the degraded underwater image. The researches about image restoration has always focused on the description of PSF, the models were all built on the basis of the ocean optics theory and small-angle forward scattering theory. The common feature of the existing models is that they all depend on the prior knowledge of underwater optics parameters, and the prior knowledge need to be acquired with standard ocean optical measurements and theoretical calculations, so the existing models are more suitable for the particular representative marine area. For the application of the real-time observation in offshore operations, the changes of dynamic environments make the prior knowledge unavailable, and on-site measurement is often a costly technical problem. To this end, we proposed a method of image restoration based on estimation which can restore the target image approximatively under the real-time and dynamic conditions only by analyzing the backscattering signals. The implementation of this method dued to the backscattering description based on the scattering multi-layer transfer model. Only with the in-site measurement of backscattering background, we can get the system parameters needed by restoration without any prior knowledge about underwater inherent optical parameters.4. We proposed a method of the target detection with the low SNR, and the method is based on the power spectrum of underwater backscattering noise. By using this method, we can obtained a better result. And the method needs no contrast of image or gray scale and size of target, so it is better than the traditional methods.