Simulating increasing image distance

Question

I have a set of aerial images, but no information about the original camera or angular resolution of the photos. I need to in some way decrease the resolution of the images in a way that simulates increasing distance. I first tried using Matlab's imresize function (with default parameters) to decimate the images by various scales, but now I'm questioning whether or not this decimation actually is the right way to simulate distance. I don't want the images to look clearer than they actually would if the distance between the camera and subject was increased.

So does anyone know if this is an adequate way to simulate distance, or if there's a more realistic way to do this?

Answer 1

In order to simulate a native resolution image at an appropriate slant range you need to start with an appropriately decimated original and then simulate sharpness loss. If not you will simulate the GSD at your extended slant range rather than the GRD. Since most aerial imaging optics are telecentric, distortion and resolution loss to the lens are generally magnification insensitive. You therefore only need to model losses to sensor MTF and atmospheric MTF.

To apply the simulated MTF loss you will need to calculate the MTF for a selected resolution of sensor. Hint: ifov and sensor size are directly proportional with focal length so you can simply guess at two variables to predict the third and then adjust altitude as you wish to obtain new GRD/GSD relationship. The blur you must apply is the ratio of GRD to GSD.

There are two ways to simulate the blur and which you use is a matter of experimentation with your software. You can either apply a mean or gaussian blur (or some mix of the two.) You can apply the blur before or after resizing. When resizing make sure to specify a method which does not sharpen. If you are using matlab you have the option of calling imresize(name,'method') Where method allows you to specify a custom kernel. This would allow you to apply gaussian or mean blurring at the time of resize.

When method is a two-element cell array, it defines a custom interpolation kernel. The cell array has the form {f,w}, where f is a function handle for a custom interpolation kernel and w is the width of the custom kernel. f(x) must be zero outside the interval -w/2 <= x < w/2. The function handle f can be called with a scalar or a vector input. For user-specified interpolation kernels, the output image can have some values slightly outside the range of pixel values in the input image.

Please note that although my answer here is correct it is incomplete. Remote Sensing Image quality modeling systems are complex and usually proprietary. To learn about the more nuanced elements of remote sensing simulation and image chain analysis I recommend Schott's Remote Sensing or Leachtenauer and Driggers' Surveillance and Reconnaissance Imaging Systems

Answer 2

Short answer: you can't do it with just one image.

Long[er] answer: to realistically simulate distance change, you need either multiple images taken from multiple different subject distances or to actually geometrically distort the original image. The reason behind this is that physically changing the distance of your subject changes your perspective of it. Resizing a single image lets you (to a certain extent) simulate zooming in and out with a lens without changing the distance.