A customer asked me last week how to do multidimensional interpolation with integer inputs. The MATLAB function interpn supports only double- and single-precision inputs. It's possible to do... 더 읽어보기 >>

I've written previously about how Image Processing Toolbox uses inverse mapping to implement spatial transforms. In this method, you set up a grid in output space. For each pixel in the... 더 읽어보기 >>

I wrote previously that most spatial image transformation implementations use inverse mapping. The Image Processing Toolbox function imtransform is implementated using this technique. Here's... 더 읽어보기 >>

I wrote last week about the forward mapping method of spatially transforming images. Because of the disadvantages of the forward mapping method, most of the practical implementations use a... 더 읽어보기 >>

I've written previously about defining a spatial transform as a function, (x,y) = T{(u,v)}, that maps points from one space (input space) to another (output space). Given such a function, how do... 더 읽어보기 >>

I've received some comments and e-mail asking how to apply the spatial transformation ideas I've been writing about to images. When I started this series, I naively assumed that Image Processing... 더 읽어보기 >>

We've talked about using Image Processing Toolbox functions to define an affine transformation and apply it to points. Let's begin to explore transforming images. ... 더 읽어보기 >>

Several Image Processing Toolbox functions related to spatial transformations use "tform" structures. A tform structure has data and function handles needed for applying a... 더 읽어보기 >>

To explore spatial transformations of images, we need a simple, nontrivial, and useful transformation. The affine transformation fits the bill. Here's the basic affine... 더 읽어보기 >>

"Terminology and notation" - is there a more boring way to start a topic? Unfortunately it's necessary, because there is a lot of variation in terms and equations from book to book and paper to... 더 읽어보기 >>