Poster Session: Study of contrast detection filters for images

In perceptual contrast imaging, which removes only the contrast information humans cannot perceive from images, detecting local contrast per frequency is essential. It is known that simple and complex cells in the primary visual cortex (V1) are involved in human contrast detection. Therefore, in this study, we experimented with filters modeled after simple and complex cells for contrast detection to determine which filter is more suitable for perceptual contrast imaging. In the experiment, we modeled simple cells with Gabor filters and complex cells with the energy model, which is the square root of the sum of the squares of two Gabor filter responses with a phase difference of π/2. We used each model for contrast detection to generate perceptual contrast images and conducted subjective evaluation experiments to assess the distinguishability between the produced perceptual contrast images and the input images. In the experiment, subjects memorized an original input image to be selected in the next step. Then, subjects selected an image they believed to be the original in a two-interval forced-choice procedure. The results show that the accuracy in the complex cell model experiments was significantly close to 0.5, indicating no visual differences between the perceptual contrast images and their original, while the experiments of the simple cell model were not. Therefore, we concluded the complex cell model is more suitable for contrast detection in perceptual contrast imaging.