Images are vague because they can be considered as sets of bright data, and brightness is a vague concept. Soft computing is a computational paradigm designed to handle and process ambiguous data. Fuzzy mathematics plays an important role in soft computing. Fuzzy techniques can effectively address the vagueness of an image. This paper proposes a nonlinear fuzzifier (NFr) and a time-efficient as well as effective fuzzy technique for image contrast enhancement with fine details preservation. First, the suggested technique fuzzifies an image with the proposed NFr. Then, it defuzzifies the fuzzified image with the inverse of a linear fuzzifier for producing the final image. The technique effectively enhances the contrast of an image and preserves its fine details by reducing its vagueness within two simple steps in a very short time. The technique has been compared with some conventional and cutting-edge contrast enhancement methods (both fuzzy and crisp) regarding eight objective image quality assessment (IQA) measures: linear index of fuzziness, discrete entropy, mean brightness preservation, bit-plane to bit-plane similarity, SSIM, PSNR, BRISQUE, and contrast improvement. Also, elapsed time and visual IQA are carried out for subjective IQA. The findings indicate the time efficiency and effectiveness of the proposed fuzzy technique in image contrast enhancement. The source code is available at https://doi.org/10.13140/RG.2.2.14716.51849 .