Grazer develops methods to combat ‘image noise’

The researcher from the University of Graz borrows from nocturnal bees and butterflies. He has packaged their method in an algorithm that removes image noise without significantly affecting image sharpness.

While conventional noise reduction filters perform several complex calculations, increasing the mathematical effort, the biologist’s method essentially requires two calculation formulas. The basis for this is the vision of insects traveling in the dark.

“They need very sensitive eyes to search for food in a targeted manner,” the scientist explains. The origin of the principle lies in the anatomy of the eyes of these small animals: both the Vienna wine hawk moth and the Panama native night bee Megalopta genalis see their surroundings well in moon and starlight and can search for food.

Hartbauer has partially modeled this sensory performance of insects in an algorithm that requires only one parameter. Although this is easier to determine, a noise reduction calculation must be performed for each pixel separately. This process currently takes longer than conventional programs.

The biologist summarizes the procedure: “In the first step, a local average filter is adaptively calculated for each pixel to remove moderate sensor noise while preserving fine image details and object contours. The second step is to improve the sharpness of the image using an unsharp mask filter.”

The publication appeared in the Journal of Imaging.