Image Interpolation using Mathematical Morphology

—We present a new method for interpolating binary images that outperforms existing techniques. Bitmapped images have a specific horizontal and vertical resolution. When we wish to magnify such an image then the resolution will be increased, allowing more details in the image. These extra details are not present in the original image. A simple blowup of the image will introduce jagged edges, also called “jaggies”. Interpolation techniques calculate the values of the new pixels that become available. These values are derived from their neighbouring picture elements. Our interpolation technique “mmINT” is based on mathematical morphology, a theoretical framework to alter an image while preserving the image objects’ geometry. The algorithm detects jaggies in the blown up image and removes them, making the edges smoother. This is done by replacing specific black pixels with white pixels, and vice versa. Keywords—Mathematical Morphology, Binary Interpolation

• Type: Conference
• Year: 2006
• Where: DIAL
• Authors: Alessandro Ledda, Hiêp Quang Luong, Wilfried Philips, Valérie De Witte, Etienne E. Kerre
• Keywords: DIAL 2006, Image, Interpolation Technique, Specific Black Pixels