Fisheye cameras or wide-angle cameras used on automobiles will have various future applications as “distributed sensors in daily transport” -- objects on roadside are frequently observed multiple times by multiple vehicles. Although the object regions are often captured with relatively low image quality (low resolution and large blur) resulting from the character of the lens, it is possible to enhance their quality by post-processing using super resolution (SR) technology. Here, it is required to decide which images to use as inputs for SR: a greater number of lower-quality images or fewer higher-quality images. We evaluated and discussed the input image quality necessary to obtain most effective SR results, especially focusing on degree of image blur. As a conclusion, we found a criterion that was related to the blur level of the initial input image of SR. Then, we considered its potential use as a requisite in observing road environments.