In this paper, we describe an improved version of our previous approach for low bit rate near- perceptually transparent image compression. The method exploits both frequency and spatial domain visual masking effects and uses a combination of Fourier and wavelet representations to encode different bands. The frequency domain masking model is based on the psychophysical masking experimental data of sinusoidal patterns while the spatial domain masking is computed with a modified version of Girod's model. A discrete cosine transform is used in conjunction with frequency domain masking to encode the low frequency subimages. The medium and high frequency subimages are encoded in the wavelet domain with spatial domain masking. The main improvement over our previous technique is that a better model is used to calculate the tolerable error level for the subimages in the wavelet domain, and a boundary control is used to prevent or reduce the ringing noise in the decoded image. This greatly improves the decoded image quality for the same coding bit rates. Experiments show the approach can achieve very high quality to nearly transparent compression at bit rates of 0.2 to 0.4 bits/pixel for the image Lena.