The purpose of this article is to prove the effectiveness of an energy subtraction image for the extraction of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to extract pulmonary nodules. Also we research influential factors to the accuracy of extraction of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones tissue such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Ribs and vessels are major causes of computer aided diagnosis (CAD) errors in extraction of pulmonary nodules and many researches have tried to solve this problem. So we select conventional X-ray images and energy subtraction X-ray images as types of images, at the same time select ${ abla}^2G$ (Laplacian of Gaussian,) filter, Min-DD (Minimum Directional Difference) and our multi-resolutional filter as types of digital filters. Also we select two performance evaluation(analysis) methods and prove the effectiveness of an energy subtraction image, the effectiveness of Min-DD filter on a conventional X-ray image and the effectiveness of multi-resolutional filter on an energy subtraction image.