11:00 〜 11:15
[PEM10-07] A penalized background subtraction model for scaling of low signal-to-noise ratio Ionogram video images
キーワード:電離圏観測、イオノグラムスケーリング、画像処理、動体検出
The upper atmosphere, known as the ionosphere, can affect shortwave communications and cause satellite positioning errors. Measuring the altitude distribution of electron density in the ionosphere, using High-Frequency radio wave reflections often causes the low signal-to-noise ratio of ionospheric echoes due to radio frequency interference. We propose a model for converting low-signal-to-noise-ratio ionospheric echo video images (Ionogram) into noise-reduced images using image processing techniques, for tracing the ionospheric echoes from Ionogram. The proposed method consists of three processing parts: STEP1. noise removal optimized for individual Ionogram images, STEP2. extraction of ionospheric echoes by penalized background subtraction technique, and STEP3. fine-tuning of ionospheric echo signals using a minimum spanning tree algorithm. For unstable signal-to-noise-ratio Ionograms, the model automatically determines the boundary threshold between signal and noise using ridge regression for STEP1 and non-fixed penalized parameters for STEP2. The proposed model successfully reproduces fine Ionograms.