Publicacións nas que colabora con Joaquín Fernández Valdivia (20)

2003

  1. Best achievable compression ratio for lossy image coding

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2652, pp. 263-270

  2. On the concept of best achievable compression ratio for lossy image coding

    Pattern Recognition, Vol. 36, Núm. 10, pp. 2377-2394

2002

  1. Coder selection for lossy compression of still images

    Pattern Recognition, Vol. 35, Núm. 11, pp. 2489-2509

  2. Optimized rate control in embedded wavelet coding

    Proceedings - International Conference on Pattern Recognition

  3. Performance of the Kullback-Leibler information gain for predicting image fidelity

    Proceedings - International Conference on Pattern Recognition

  4. Rational systems exhibit moderate risk aversion with respect to "gambles" on variable-resolution compression

    Optical Engineering, Vol. 41, Núm. 9, pp. 2216-2237

2001

  1. Computational Models for Predicting Visual Target Distinctness

    SPIE, The International Society for Optics and Photonics,

  2. Information theoretic measure for visual target distinctness

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, Núm. 4, pp. 362-383

  3. Minimum error gain for predicting visual target distinctness

    Optical Engineering, Vol. 40, Núm. 9, pp. 1794-1817

1999

  1. The RGFF representational model: a system for the automatically learned partitioning of visual patterns in digital images

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, Núm. 10, pp. 1044-1073

1998

  1. A new image distortion measure based on a data-driven multisensor organization

    Pattern Recognition, Vol. 31, Núm. 8, pp. 1099-1116

  2. A perceptual measure to predict the visual distinction between two color images

    Pattern Recognition Letters, Vol. 19, Núm. 12, pp. 1137-1152

  3. The selection of natural scales in 2D images using adaptive Gabor Filtering

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, Núm. 5, pp. 458-469

  4. Using models of feature perception in distortion measure guidance

    Pattern Recognition Letters, Vol. 19, Núm. 1, pp. 77-88