Section III introduces two new IR target image quality metrics, namely interference degree of global background (IDGB) and similarity degree of local background (SDLB), reflect the complexity of target detection in IR target image.
Similarity degree of local background (SDLB) is a quantify metric which is used to reflect the differences between target and its local background.
SDLB = IS x GS = (2[[mu].sub.L][[mu].sub.L]/[[mu].sup.2.sub.L] + [[mu].sup.2.sub.T]) x (2[[sigma].sub.T][[sigma].sub.L]/[[sigma].sup.2.sub.L] + [[sigma].sup.2.sub.T]).
One hundred and sixty actual infrared target images are used to evaluate the validity of metrics IDGB and SDLB. The size of these images is 256 x 256 pixels.
7(d), it could be concluded that IDGB and SDLB are both validity for the quality evaluation of infrared target image and could give an accurate measurement of interference to target detection.
We use twenty-four sets of actual infrared images to compare the performance of proposed metrics IDGB and SDLB with the traditional metrics, and each set is consisted of 3 to 5 images which have different backgrounds but the same target.
The proposed metrics IDGB and SDLB show that the image with the best quality is Fig.
In order to compare the performances of the proposed metrics IDGB and SDLB with the traditional metrics when evaluating the infrared images which have the same background but different targets, we add targets T1, T2 and T3, and synthesis three images shown in Fig.
IDGB and SDLB could also give the right order of image quality.
In the field of image signal processing, metrics IDGB and SDLB are proposed in this paper to measure the infrared target image based on analysing disturbance factors in target detection.