The wavelet transform theory emerged in recent years has been applied in many fields, such as image compression, edge and feature detection, image enhancement and texture analysis. We have studied some of the developments that lead to the current state of image enhancement, sufficiently considering the configurations of video image and eyespot requirement. This paper presents a new method to accentuate image using multi-scale analysis, time-frequency wavelet transform and minimum distance criteria. After decomposing an image into components of different size, position, and orientation, the amplitude of coefficients in the wavelet transform domain can be altered prior to obtaining the inverse transform. This can selectively accentuate interesting components at the expense of undesirable ones. Experimental results have shown that simpler algorithm, faster running speed, rather improved SNR and contrast can be obtained with this method, resulting in a good enhancement effect.