基于小波的非线性模型的孔探图像压缩

针对涡轮发动机内部图像细节丰富的特点,为了实现在高压缩比下对细节信息的保留,以不影响发动机内部故障检测,采用小波域的非线性表示和建模方法,利用多尺度边缘检测对边缘进行定位,通过轮廓加剖面模型在定位的边缘进行边缘影响区域划分;之后通过阈值将边缘影响区域进一步划分为较重影响系数区域与较轻影响系数区域,在不同区域应用不同的编码质量控制,从而实现了一种基于小波着重于边缘的图像编码系统.实验结果表明,与一般的小波图像压缩方法相比较,在不同的压缩率下,峰值信噪比均得到小幅度的提高,并且从视觉感官上也得到较好的效果. 

Wavelet and nonlinear model based borescope image compression

The borescope image quality around edges is very important to the fault diagnostic of aeronautic engine.And inside the turbofan engine,the borescope image often has complex edges and textures.To achieve high compression ratio without losing of the edge and texture information,a kind of image compression method with emphasis on edges and textures was presented.First,it used wavelet transform in order to obtain a set of biorthogonal subclasses of images.Second,multiscale Canny edge detector was used to locate the edge.Third,the AOI(area of influence) was set by contour plus profile model,witch was an edge nonlinear represent and modeling method.Finally,by rate control,different image quality was obtained in different areas of the image,like ROI(region-of-interest) coding of JPEG2000.Test result shows,comparing with general image compression method,at different compression ratio,PSNR(peak signal to noise ratio) has all gotten lightweight raise,and the visual perception around edges is also better than the general method.