Image Enhancement Algorithm for the Non-destructive Inspection of Energy Storage Batteries

The energy storage industry has ushered in a period of rapid development, and the emphasis on energy storage safety is also increasing. It is of great significance to non-invasively detect the state of energy storage batteries, that is, to analyze the battery using images. The clarity and precision of the image are the keys to study the internal structure of the energy storage battery. In order to achieve better image processing effect, an improved image enhancement algorithm based on fuzzy sets, histogram and contrast-limited adaptive histogram equalization (CLAHE) was raised. The algorithm proposes a comprehensive solution to the problems of rapidly acquired x-ray cell images, taking the problems of noise, contrast and local details into account. In addition to the basic function of removing noise, this algorithm can not only achieve low-contrast X-ray image correction, but also achieve image detail enhancement, which can significantly improve the signal to noise ratio (SNR) of X-ray. The proposed method is analyzed and it is shown that after the utilization of the algorithm, the X-ray image have a better gray distribution, and the SNR of the dark area image improved.