This thesis provides alternatives to the explanation that spatial filtering isresponsible for the perception of illusory contours in the Kanisza Triangle illusion. Specifically, we use a Multiresolution Wavelet Decomposition to divide an image into spatial-frequency bands that are used as inputs to three biologically motivated models. The thesis includes a brief tutorial of Wavelet theory and an in-depth explanation of our implementation of recently published algorithms for Multiresolution Wavelet Analysis. The first model is based on the saccadic movements of the human eye. It demonstrates the importance of the high spatial-frequency content of an image in the formulation of the illusion. The second model is based on the serial architecture of the data transmission channel between the retina and the visual world model. The third model considers only the high spatial-frequency content of the image. It consists of lateral excitation networks that serve to simulate the local high spatial-frequency energy interactions that contribute to illusory contours.
展开▼
