In recent years, as a result of the development of the network and popularization of the multimedia information, watermark technology has been utilized for ensuring the copyright of digital information. This paper proposed a new blind watermarking algorithm for discrete cosine transform (DCT) based digital images. In the proposed method, the differences of DCT coefficients between original and watermarked information were calculated and performed to determine the adjustment of the watermarked DCT coefficients. Simulation results show that the proposed watermark algorithm not only provided similar robustness as previous watermarking investigations but also improved image quality of the watermarked image and the quantity of hiding information. Moreover, the original image is unnecessary for acquiring the watermark information. In the reconstruction procedure, only two bytes side information was required for digital image codec. The file size of watermarked JPEG compressed image approximates one without watermarking.

This paper employs the image retrieval technique to classify breast tumors as benign or malignant lesions. We evaluated 600 ultrasound (US) images of pathologically proven solid breast nodules including 230 malignant and 370 benign tumors. The US images were acquired from four different ultrasound systems. Firstly, the physician located regions-of-interest (ROI) of ultrasound images. The textual features from ROI sub-image are utilized to classify breast tumors. The principal component analysis (PCA) is used to reduce the dimension of textual feature vector and then the image retrieval technique was utilized to differentiate between benign and malignant tumors. Historical cases can be directly added into the database and training of the diagnosis system again is not needed. The accuracy of the proposed computer-aided diagnosis (CAD) system was 91.2%, the sensitivity was 97.0% and the specificity was 87.6%. This system differentiates solid breast nodules with a relatively high accuracy in the different US systems and helps inexperienced operators avoid misdiagnosis.

The multiresolution wavelet transform has been shown to be an effective technique and achieved very good performance for texture analysis. However, a large number of images are compressed by methods based on the discrete cosine transform (DCT). Hence, the image decompression of the inverse DCT is needed to obtain the texture features based on the wavelet transform for the DCT-coded image. This paper proposes the use of the multiresolution reordered features for texture analysis. The proposed features are directly generated by using the DCT coefficients from the DCT-coded image. Comparisons with the subband-energy features extracted from the wavelet transform, conventional DCT using the Brodatz (1966) texture database indicate that the proposed method provides the best texture pattern retrieval accuracy and obtains a much better correct classification rate. The proposed DCT based features are expected to be very useful and efficient for texture pattern retrieval and classification in large DCT-coded image databases.

We present nonlinear interpolation schemes for image resolution enhancement. The multilayer perceptron (MLP) interpolation schemes based on the wavelet transform and subband filtering are proposed. Because estimating each subimage signal is more effective than estimating the whole image signal, pixels in the low-resolution image are used as the input signal of the MLP to estimate all of the wavelet subimage of the corresponding high-resolution image. The image of increased resolution is finally produced by the synthesis procedure of the wavelet transform. As compared with other popular methods, the results show that the improvement is remarkable.

Subband coding (SBC) with vector quantization (VQ) has been shown to be an effective method for coding images at low bit rates. We split the image spectrum into seven nonuniform subbands. Threshold vector quantization (TVQ) and finite state vector quantization (FSVQ) methods are employed in coding the subband images by exploiting interband and intraband correlations. Our new SBC-FSVQ schemes have the advantages of the subband-VQ scheme while reducing the bit rate and improving the image quality. Experimental results are given and comparisons are made using our new scheme and some other coding techniques. In the experiments, it is found that SBC-FSVQ schemes achieve the best peak signal-to-noise ratio (PSNR) performance when compared to other methods at the same bit rate.