Novel Framework for Knee Arthroscopic Image Enhancement

An arthroscope is a tool for allowing an endoscope to be inserted directly into the inside of a joint to observe its structure, in contrast to X-rays, computed tomography, and magnetic resonance imaging, which directly capture pictures of a joint. Therefore, it can effectively treat joint diseases by identifying causes of pain that are not found by, e.g., computed tomography and magnetic resonance imaging. However, joint endoscopy has a very high cost, is very burdensome for patients, and has problems in regards to infection when being re-used. Thus, we developed disposable joint endoscopic camera modules for preventing re-use and infection, and researched approaches to reducing patient waiting times and cost burdens. In that regard, it is necessary to improve the brightness and color of the images, as they are used for compacting and disposal of the camera modules. In addition, we studied methods for improving automatic images, as image colors may vary (owing to blood or other foreign substances) when observed using the arthroscope. The proposed framework is divided into two sequences. First, we perform a histogram modification algorithm as an image enhancement technique. This results in a brightness optimization effect on the arthroscopic image. Second, we conduct a high saturation color mapping before proceeding to the next step. In particular, one of the reference points for diagnosing a disease is color information; thus, the improvement of color saturation is considered first in the color mapping. The proposed method provides better brightness values while preserving color information.