A pixel domain algorithm for low complexity perceptual image coding is proposed. The algorithm exploits a combination of downsampling, predictive coding and just-noticeable difference (JND) model. Downsampling is performed adaptively on the input image based on regions-of-interest (ROI) identified by measuring the downsampling distortions against the visibility thresholds given by the JND model. The downsampled pixel is encoded if the differences are within the JND thresholds, and otherwise the original pixels are encoded with a quantization parameter selected based on the JND model. Noise shaping is employed to suppress potential visual artifacts due to quantization error propagation. The coding error at any pixel location can be guaranteed to be within the corresponding JND threshold. Experimental results show improved rate-distortion performance and visual quality over JPEG-LS as well as reduced rates compared with other standard codecs like JPEG 2000 at the same PSPNR.