Human visual system allocates different amounts of processing resources to different portions of the visual field, and in fact, features will only be perceived if they success in attracting attention. Hence, if the compressed images are going to be used for recognition purposes, then it is desirable to preserve the features during the progressive transmission. In such cases, a selection of significant features might be used to guide the image transmission. To this aim, we have developed an algorithm called as "Feature-based Rational Embedded Wavelet Image Coder (FREWIC)" in which we have reformulated the rational embedded wavelet image coding to base the quantizer formation on features extracted by a local energy model which is capable of successfully explaining a reasonable number of psychophysical effects in human feature perception.