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Aliasing and blurring in microscanned imagery

机译:微扫描图像中的混叠和模糊

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Abstract: Electro-optic staring sensors, which sample a scene with pixels of finite size, generate images that are affected by aliasing and blurring caused by the sampling process. One potential method to reduce the effects of sampling is microscanning. In the microscan process, multiple images of the scene are generated. Between each successive image, the location of the image on the detector array is moved a fraction of a pixel. The set of images produced in the microscan process are then combined to form a single image. We present an analytical model of the microscan process. The model shows that the microscan process can significantly reduce aliasing in the reconstructed image, and that the process does not blur the image beyond the blur caused by the finite pixel aperture. The model also shows that factors such as the blur produced by the imaging optics and the fill factor of the detector array affect the reduction in aliasing produced by microscanning. We present a quantitative description of the effect of microscanning for selected cases of fill factor, optics blur, and number of microscan steps. We also present images produced by computer simulation which qualitatively verify the reduction in aliasing associated with the microscan process.!9
机译:摘要:电光凝视传感器对像素有限的场景进行采样,生成的图像受采样过程中的混叠和模糊影响。减少采样影响的一种潜在方法是微扫描。在微扫描过程中,将生成场景的多个图像。在每个连续图像之间,图像在检测器阵列上的位置移动了一个像素的一部分。然后,将在微扫描过程中生成的图像集进行合并以形成单个图像。我们提出了微扫描过程的分析模型。该模型表明,微扫描过程可以显着减少重建图像中的混叠现象,并且该过程不会使图像模糊超出有限像素孔径所造成的模糊。该模型还表明,诸如由成像光学器件产生的模糊和检测器阵列的填充因子之类的因素会影响由微扫描产生的混叠的减少。我们对所选的填充因子,光学模糊和微扫描步骤数的情况进行了微扫描效果的定量描述。我们还介绍了通过计算机模拟产生的图像,该图像定性地验证了与微扫描过程相关的混叠的减少。9

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