This paper emphasizes on designing of a novice quantizer that is more suitable for compressing images through new transform known as curvelet transform. The new transform is believed to capture image information more efficiently than the wavelet transform by providing basis elements in addition to possessing the qualities of wavelet. It was designed to represent edges and other singularities along curves much more efficiently than traditional transforms, i.e. using many fewer coefficients for a given accuracy of reconstruction. This compression algorithm is tested on various images like plain, textured and building images. The results are compared with the existing techniques like curvelet with existing quatizer, wavelet with existing quantizer and wavelet with proposed quantzer. The proposed algorithm “curvelets with proposed quantizer” outperforms the existing techniques. The performance is evaluated through visual clarity, Peak Signal to Noise Ratio (PSNR) and compression metrics such as Compression ratio and Bit-rate.