Infrared target detection and recognition are investigated by considering the wide application requirements of an airborne photoelectric system. The proposed algorithm can be divided into three parts. First, on the basis that the target of infrared images dominates the background in the frequency domain, this paper presents a method of candidate region detection. The detection algorithm first generates a saliency map using the discrete cosine transform and then identifies candidate regions by computing and comparing saliency scores of different regions. Second, to extract the features of each candidate region for recognition, the paper presents a local descriptor and subsequently uses locality-constrained linear coding and a pooling operator to obtain the feature vector of the target, and then further completes target recognition via a simple linear classifier. Finally, as preliminary research on the engineering application of related algorithms, the detection and recognition algorithms are transplanted to an embedded platform. The paper conducts experiments on six test sequences to evaluate the performance of the proposed algorithms and the computing efficiency on the embedded platform. An evaluation experiment and comparison experiment verify the effectiveness and practicability of the proposed algorithms.