The use of smartphone cameras for capturing photographs has seen an exponential growth in the last decade. The noise present in these photographs significantly deviates from the popular Independently Identically Distributed (i.i.d.) Additive White Gaussian Noise (AWGN) noise, and thus the conclusions drawn from simulated-AWGN cannot be directly applied to the smartphone’s true noise. This paper is the first reporting of the exhibition of Stochastic Resonance (SR) or noise-induced threshold-crossing in three genres of discontinuity detectors used in image processing — corner detector, line detector, and edge detector for real-world smartphone images. For the images under investigation, the performance of these detectors is quantified w.r.t. parameters representing intrinsic noise. Observations suggest that all these detectors inherently exhibit the phenomenon of SR due to the fundamental assistance offered by controlled amount of noise in crossing detector thresholds. The manifestations of SR — constant parameter value with varying noise and varying parameter value with constant noise — are demonstrated to exhibit SR in each of the three detectors.