We briefly describe and compare some recent advances in image denoising. In particular, we discuss three leading denoising algorithms, and describe their similarities and differences in terms of both structure and performance. Following a summary of each of these methods, several examples with various images corrupted with simulated and real noise of different strengths are presented. With the help of these experiments, we are able to identify the strengths and weaknesses of these state of the art methods, as well as seek the way ahead towards a definitive solution to the long-standing problem of image denoising.