To satisfy the demand of rich-resin defect detection in the so-called low-porosity carbon fiber reinforced composite (CFRP) with porosity close to zero, an ultrasonic testing methodology was proposed in this article. The denoising methods, attenuation suppression method, and 3D imaging technology for rich-resin identification are investigated, and low-porosity CFRP rich-resin detection software was developed. The rich resin was detected in four steps. First, the resonant frequency was estimated, and the high-frequency stochastic noise was suppressed. Second, variational mode decomposition (VMD) was used to separate the resonant structure noise and extract the low-frequency component. The low-frequency component consisted of the front-wall echo, back-wall echo, rich-resin reflection signal, and remaining coherent noise made up of the interlayer reflection signals and material scattering noise. Third, the instant amplitude ratio was introduced to correct the envelop attenuation of the low-frequency component and describe the local reflectivity of the low-porosity CFRP. Finally, the multi-threshold Otsu method was used to search the threshold of the rich-resin detection, resulting in the elimination of interference and finishing the detection of rich resin. Further, multi-view imaging was performed on the test results, and the rich resin was identified in the 3D, C-scan, and B-scan imaging processes. The experimental results show that when the VMD mode was set to two and the classes in the multi-threshold Otsu method are set to three, a rich-resin reflection signal can be detected. When the threshold in the multi-view imaging is set to 0.15, the rich resin can be effectively characterized.