【作者】 刘晓东；

【导师】 张歆；

【作者基本信息】 西北工业大学 ， 通信与信息系统， 2007， 硕士

【摘要】 随着海洋资源的开发和国防建设的需要，视频探测作为一种重要的水下目标非声探测识别的有效手段受到了广泛的重视。近几年，自主水下航行器(AUV)和水声通信技术的飞速发展进一步推动了人们对水下视频图像领域的研究。 在视频探测系统中，如何将视频探测数据有效存储，或经由水声信道或无线电信道实时、有效地传输到图像处理系统是其中的基础和关键技术之一。由于水声信道带宽严重受限特性及AUV图像数据存储空间有限等影响，使得视频图像压缩编码成为水下目标视觉识别应用的关键技术。小波变换具有较好的时频局部化性能和与人眼视觉特性相符合的多分辨率分析能力，因而被广泛应用于图像压缩中。 本文根据水下目标视觉探测识别应用的需要，对基于小波变换的水下视频图像压缩编码进行了初步研究。论文首先介绍了小波变换的基本理论，分析了小波图像的特点以及小波基的性质，研究了运动补偿预测技术和嵌入式小波零树编码算法及其改进算法。针对小波基性质对图像压缩编码的影响，采用不同小波基进行图像压缩重构实验，证明具有线性相位的双正交小波更适合图像压缩。由于AUV在水下运动较慢，其所采集的连续帧图像内象素块具有较强相关性的特点，根据几种运动估计算法的实验，证明了自适应十字搜索法更加适合水下视频图像进行运动估计。针对水下图像低对比度和细节模糊等特点，对嵌入式小波零树编码算法进行了改进。论文最后结合小波图像编码算法和运动估计补偿预测实现了水下视频图像压缩编码系统设计，由实验结果证明整个系统方案的有效性。更多还原

【Abstract】 With the exploitation of ocean and the need of national defence, visual detection technology as an effectively supporting of underwater non-acoustic detection was received broad attention. In recent years, advances in autonomous underwater vehicle (AUV) and underwater communication technology had promoted a surge of research in the field of underwater video.Effective data storage and data transmission in acoustic or radio channel were the basis of visual detection. Due to limited bandwidth of acoustic channel and storage space for video data, underwater video compression technology became the key to underwater visual detection. Because of the better time-frequency localization and multiresolution analysis, wavelet transform was widely used in image compression.With the need of underwater visual detection, wavelet-based underwater video compression was introduced in this paper. The basic theory of wavelet transform and the characteristics of wavelet image were analyzed at first. Then motion compensated prediction and embedded zerotrees wavelet algorithm were studied. Because of linear phase, biorthogonal wavelet is more appropriate than single-orthogonal wavelet in image compression. Because of the slow motion of AUV, the underwater video had strong correlation. After analysis several motion estimation algorithms, adaptive rood pattern search method was more suitable for underwater video compression. According to the low contrast and low detailed nature of underwater image, embedded zerotrees coding algorithm was improved in this paper. Combined with motion compensated prediction, wavelet-based underwater video compression was designed. According to the experiment of underwater video compression, the algorithm in this paper was met requirements.更多还原